= Cambridge University Undergradaute Research Opportunities Programme - UROP

UROP Projects

The UROP is open. Available projects are to be emailed to Vicky Houghton to be posted. All candidates are to follow the application process for the project/s you are applying for.


Application Restrictions EPSRC funded Projects
The UROP is designed to support undergraduates studying at the University of Cambridge who are going to return for at least one more year of undergraduate study.
Final Year undergraduates and Postgraduate students should not apply.

For projects that are EPSRC funded and marked with the blue flag,  European Union citizens ONLY students must meet certain criteria to apply.

( See LINK for criteria )

For EPSRC funded projects, students should be in the middle years of a first degree within EPSRC's technological remit.


Information for Cambridge University students


Information for Cambridge University Staff

Please report any broken links to UROP Web Page Co-ordinator

Ms Vicky Houghton


Accelerating Zero Carbon Flight

Lead Supervisor: Prof. Rob Miller, Whittle Lab, Department of Engineering
Project Available

Project Description:

Aviation is one of the hardest sectors to decarbonise. If nothing is done, the sector will come under increased, and volatile pressure, forcing it to dramatically reduce the number of commercial flights. The longer it goes before the aviation sector addresses this problem the greater the threat. This threatens the current democratisation of long-distance air travel and threatens to return us to a situation where only the rich can afford to travel. The time scales for action are incredibly short when compared to innovation cycles in the industry. The aim of this research is to bring together technology, policy, infrastructure and investment knowledge to develop a strategy for accelerating the decarbonisation of flight.

The project will require multidisciplinary teams to be formed and UROPS will be supervised by:

Whittle Laboratory - Prof Rob Miller, Dr Chez Hall, Tony Purnell, Dr Tony Dickens, Dr Nick Atkins, Dr Maria Vera

Cambridge Institute of Sustainable Leadership - Dame Polly Courtice, Dr Eliot Whittington

Chemical Engineering and Engineering - Prof John Dennis, Dr Stuart Scott, Dr Ewa Marek, Prof Alex Routh, Dr Paul Hodgson

  • We are looking for students who have just finished their 2nd and 3rd years with skills in the areas such as aerospace, chemical engineering, electrical, economics, systems modelling.
  • The UROPS will work for around 10 weeks (to be agreed flexibly). They will work remotely, regularly linking into the team or with industry partners.
  • Please send your application to Juliet Teather to apply or for further information.

  • Insertion Date: 25 June 2020


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    Dynamics of granular anisotropic shapes - Experiments & Theory

    Lead Supervisor: Prof. Erika Eiser, Department of Physics
    Project Available

    Project Description:

    Some 20 years ago the famous Brazil-nut problem and its reverse counterpart had been solved [1-3]. The question this problem posed was why mixtures of large and small spheres demix, with the large one always ending up on top of a container when shaken vertically - just like in a package of muesli. Similar to thermodynamic systems (gases and fluids), granular media are many body problems. However, unlike for the former one cannot define a temperature in granular systems, as their motion is dominated by gravity and not thermal motion. However, by vertically shaking a binary granular system one induces a quasi-temperature that is particle size dependent, which leads to a convective separation.

    In this project the student will examine the dynamics of a 2D arrangement of Y- and X-shaped granular particles placed on a flat, vibrating table. Similar to solutions of such asymmetric, concave particles (a nano-scopic equivalent is made of DNA-nanostars) the student will investigate the configurational space of these particles in the dilute (non-touching), overlap (touching) and semi-dilute (overlapping) regime. This will involve first setting up the experiment and subsequently the video-analysis of these systems for different shaking amplitudes and frequencies and developing a theory for understanding the diffusivity of individual particles under different concentration and 'virtual temperature' conditions. The work will be done with material prepared by the group and using a vibration-equipment ready to use. The desired shapes will be produced through 3D-printing in a collaboration with the group of Prof. Adjey Sood, at the JNCR Bangalore, India.

    References

    [1] D. C. Hong et al. Phys. Rev. Lett. 86, 3423 (2001)

    [2] D. A. Huerta & J. C. Ruiz-Suarez Phys. Rev. Lett. 92, 114301 (2004)

    [3] A.P.J. Breu, H.-M. Ensner, C.A. Kruelle, and I. Rehberg, Phys. Rev. Lett. 90, 014302 (2003)

  • The project will be co-supervised with David King
  • If interested, please contact Prof. Erika Eiser

  • Insertion Date: 16 March 2020


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    Source Brightness Measurements for Helium Atom Microscopy

    Lead Supervisor: Dr Andrew Jardine at the Department of Physics
    Project Available

    Project Description:

    Scanning helium microscopy (SHeM) is an exciting new form of microscopy for imaging delicate surfaces, and is the subject of a £1M research programme within the SMF group at the Cavendish Laboratory. The brightness of the helium source plays a crucial role in determining image quality, and is determined by a variety of thermodynamic and (both classical and quantum) scattering processes around the supersonic helium expansion.

    The aim of this project is to experimentally characterise the brightness of the virtual helium source for the new microscope, under a variety of different pressure and flow conditions. The data will be compared to existing models, and will be used to determine the operating conditions in all future instruments.The project will involve hands on laboratory work and subsequent analysis.

  • Tripos experience in a scientific or engineering discipline, and an interest experimental physics research is essential.Experience of at least Part IB Physics, or equivalent, is highly desirable.
  • The project will not be allocated before 24th April 2020.
  • This project will be co-supervised with and Dr David Ward from the Department of Physics.
  • If interested, please contact Dr Andrew Jardine as soon as possible.

  • Insertion Date: 11 March 2020


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    Giving hydrogels decompression sickness ("the bends")

    Lead Supervisors: Dr Adrien Lefauve and Dr Merlin Etzold at the Department of Applied Mathematics and Theoretical Physics
    Project Available

     European Union citizens ONLY EPSRC criteria may apply CLICK HERE for criteria

    Project on hold till further notice:

    This project is motivated by our desire to obtain a fundamental understanding of decompression sickness in scuba diving. This life-threatening condition occurs as a result of nitrogen dissolved at high pressure in body tissues (when diving at depth) forming bubbles minutes to hours after the pressure is decreased when resurfacing.

    In this project, we will explore the phenomenon of bubble formation when depressurising soft hydrogels containing high levels of dissolved gases. Just as when a bottle of fizzy drink is opened, bubbles will tend to form and grow in such soft materials, but their elasticity provides an opposing force that gives rise to a range of interesting behaviours. By carrying out a range of experiments with varying parameters, you will observe and quantify these behaviours to guide the future mathematical modelling of this problem.

    The project will be mainly experimental and will be based in the G. K. Batchelor Laboratory in the Centre for Mathematical Sciences. During this research project you will gain independence in carrying out and analysing exciting experiments with real-life applications. You will also learn to use empirical observations to start the process of mathematical modelling and exercise your written and oral communication skills.

  • The project is well suited for students with interests in fluid and solid mechanics, (physical) chemistry, or mathematical modelling.
  • Some basic programming knowledge in high level languages such as Python or Matlab for data and image analysis will be necessary to conduct this project.
  • We ask you to spend your summer in a lab (which is often dark) and develop our ideas, so we are looking for an enthusiastic experimentalist who likes to tinker and play with ideas.
  • Interest in scuba diving and/or medical physics would be a bonus.
  • Expected duration of the project is 8 weeks starting mid or late June 2020.
  • Please contact Dr Adrien Lefauve and Dr Merlin Etzold as soon as possible or for further information.

  • Insertion Date: 11 March 2020


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    Neural network representation of quantum many-body states

    Lead Supervisor: Dr Sergii Strelchuk, Department of Applied Mathematics and Theoretical Physics
    Project Available

     European Union citizens ONLY EPSRC criteria may apply CLICK HERE for criteria

    Project on hold till further notice:

    The wave function contains all the information about the properties of a quantum system. One needs an exponentially large amount of information to represent fully a wave function of a general many-body system. This makes it immensely difficult to simulate these systems using classical approaches. Surprisingly, in many practically interesting situations, one can efficiently represent the wave function with the help of artificial neural networks (such as (Restricted) Boltzmann Machines) -- even when no known classical algorithm exists. RBMs proved to be remarkably versatile when it comes to efficiently representing states of a diverse range of physical systems. In recent years, there were several examples of ground states of certain quantum systems where such efficient representations are unlikely to exist.

    In our project, we will consider several quantum systems of practical importance that are described by the respective Hamiltonian for which such representations are not known to exist. We will numerically investigate the possibility of efficient neural-network representations and, if successful, attempt to classify rigorously which families of ground states admit efficient low-dimensional RBM representations. We will run numerical experiments on a specialized GPUs (2x GeForce RTX 2080ti).

  • An interest and background in quantum information and quantum computing is essential, as is a strong background in python programming. Experience with neural-network programming is desirable but not essential.
  • You will gain practical skills in implementing modern RBM neural-network architecture and learn how to apply them to real-world systems in quantum physics. Additionally, you will learn about quantum complexity theory and its connections to quantum information and quantum computing.
  • Expected duration of the project is 8 weeks.
  • Please contact Dr Sergii Strelchuk to apply or for further information.

  • Insertion Date: 11 March 2020


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    Vibration testing of 3D printed structures

    Lead Supervisor: Professor Robin Langley, Department of Engineering
    Project Available

    Project Description:

    The Dynamics and Vibration Research Group currently has a research project with Mitsubishi Heavy Industries (MHI) on vibration mitigation in structures that use stiffened panels: for example, aircraft, spacecraft launch vehicles, and ships. The stiffeners are present mainly for structural strength reasons, but by making small adjustments to the position of the stiffeners it is possible that a significant reduction in vibration transmission can be achieved (from the engine room to a passenger cabin in a cruise liner for example). We have an ongoing programme of theoretical and computational work, but the plan for the UROP is to use 3D priniting to produce a number of panel designs and perform vibration testing on each one. The student could also get involved in the computational modelling work if motivated to do so.

  • There will be an opportunity for the student to learn 3D printing techniques and vibration testing, but a strong interest in these areas would be essential, together with an interest in the application areas.
  • The dates for the work over the summer would be flexible.
  • The project is being co-supervised with Dr Tore Butlin.
  • The work has the potential to be continued as a 4th year project.
  • If interested, please contact Professor Robin Langley before 28th February 2020.

  • Insertion Date: 18 February 2020


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    Learning 3D Printers

    Lead Supervisor: Dr. Sebastian Pattinson, Institute for Manufacturing, Department of Engineering
    Project Available

     European Union citizens ONLY EPSRC criteria may apply CLICK HERE for criteria

    Project Description:

    3D printing is a relatively novel technique where parts are built by the layer-by-layer deposition of material. It offers virtually limitless opportunities to design and manufacture devices because it enables the control of geometry, material composition, and processing conditions at every point in an individual object. There is thus considerable excitement over the potential for 3D printing make better materials and devices, including through the use of complex and locally varying structure. Optimizing across such a large parameter space is difficult, though, and novel learning techniques are likely key to addressing this challenge.

    This project will involve working with the group to build novel learning 3D printing systems and developing their capabilities across different materials. There will be opportunities for hardware, software, and material development.

  • This project taking place is subject to securing funding.
  • Background knowledge of 3D printing, electronics, software development, materials, is useful but not essential.
  • Period of the project: 8-10 weeks.
  • The project will be based at the Institute for Manufacturing.
  • If interested, please contact Dr. Sebastian Pattinson, as early as possible.

  • Insertion Date: 12 February 2020


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    Flow of glacial ice sheets over deformable material

    Lead Supervisor: Dr Katarzyna Kowal, Department of Applied Mathematics and Theoretical Physics
    Project Available

    Project on hold till further notice:

    The ice sheet of West Antarctica alone has the potential to raise sea levels by about 7 metres should it become unstable and flow rapidly into the ocean in response to global warming, altering coast lines and metropolitan areas as we know them today. Such sea level rise can result from the dynamics of ice sheets, alone, and depends greatly on conditions underneath the ice, causing rapid acceleration in ice discharge and melt rates. In particular, glacial ice sheets flow over unconsolidated, water-saturated subglacial sediment that serves to lubricate the base of the ice and accelerate the flow of ice towards the ocean.

    The project seeks to explore the dependence of the flow of viscous fluids, such as glacial ice sheets on the large scale, on what lubricates it from below and on the accumulation of the underlying material.

    There will be the opportunity for designing and conducting small-scale fluid-dynamical laboratory experiments involving viscous fluids, such as syrup as well as the opportunity to model the flow mathematically from first principles. Guidance on laboratory experiments and mathematical modelling will be provided.

    The project will be based in the G. K. Batchelor Laboratory of the Department of Applied Mathematics and Theoretical Physics

  • Background knowledge of fluid mechanics (such as from an introductory course on fluid mechanics) is useful but not essential as the project is self-contained.
  • Period of the Project: 8-10 weeks.
  • If interested, please contact Dr Katarzyna Kowal, as early as possible.

  • Insertion Date: 6 February 2020


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    Dynamics of lubricated ice-sheet grounding zones

    Lead Supervisor: Dr Katarzyna Kowal, Department of Applied Mathematics and Theoretical Physics
    Project Available

    Project on hold till further notice:

    The stability of marine ice sheets, such as those of West Antarctica, depends heavily on the dynamics of ice-sheet grounding zones - regions separating grounded ice sheets, in contact with the bedrock, from freely floating ice shelves. Curiously, it has been found that subglacial till (a mixture of water, clay and subglacial sediment) that lubricates the base of ice streams accumulates into sedimentary wedges, or till-deltas, in these grounding zones. Such sedimentation can have immediate consequences in stabilizing grounding zones against retreat in response to rising sea levels.

    The aim of the project is to explore the formation of grounding zone wedges and their effect on the large-scale dynamics of ice sheets using principles of viscous fluid mechanics. There will be the opportunity for designing and conducting small-scale fluid-dynamical laboratory experiments involving viscous fluids, such as syrup, as well as the opportunity to model the flow mathematically from first principles. Guidance on laboratory experiments and mathematical modelling will be provided.

    The project will be based in the G. K. Batchelor Laboratory of the Department of Applied Mathematics and Theoretical Physics

  • Background knowledge of fluid mechanics (such as from an introductory course on fluid mechanics) is useful but not essential as the project is self-contained.
  • Period of the Project: 8-10 weeks.
  • If interested, please contact Dr Katarzyna Kowal, as early as possible.

  • Insertion Date: 6 February 2020


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    Control of viscous fingering instabilities

    Lead Supervisor: Dr Katarzyna Kowal, Department of Applied Mathematics and Theoretical Physics
    Project Available

    Project on hold till further notice:

    The interface between two fluids can be made morphologically unstable, resulting in complex pattern formation frequently encountered in porous media and biological systems. Such phenomena are widespread in nature and industry, ranging from crude oil recovery, hydrology, and filtration, to the self-organisation of collective biological systems and medical applications. In most cases, these instabilities occur when a less viscous fluid displaces a more viscous fluid, for example water displacing syrup, either by injection or by gravity when the interface separates two fluids of different densities.

    As it is advantageous to suppress these instabilities for a number of industrial applications, the aim of the project is to understand the control mechanisms behind stabilising such interfacial fingering patterns. There will be the opportunity for designing and conducting small-scale fluid-dynamical laboratory experiments involving viscous fluids, such as syrup as well as the opportunity to model the flow mathematically from first principles. Guidance on laboratory experiments and mathematical modelling will be provided.

    The project will be based in the G. K. Batchelor Laboratory of the Department of Applied Mathematics and Theoretical Physics

  • Background knowledge of fluid mechanics (such as from an introductory course on fluid mechanics) is useful but not essential as the project is self-contained.
  • Period of the Project: 8-10 weeks.
  • If interested, please contact Dr Katarzyna Kowal, as early as possible.

  • Insertion Date: 6 February 2020


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    Amorphous materials for quantum computers?

    Lead Supervisor: Prof Lindsay Greer, Department of Materials Science. Co-supervisor: Dr Jonathan Bean, Department of Materials Science.
    Project Available

    Project Description:

    Technology changes our lives, allows access to new experiences, accelerates learning. The advent of quantum computers promises to change the way we live and work significantly but the power usage of these new machines is extremely high due to the cold temperatures these machines required to operate.

    This is a computational project which aims to automatically screen a large number of possible alternatives to the Josephson junctions which comprise modern day machines. We will be using non-equilibrium greens function (NEGF) quantum mechanics and the SIESTA/Quantum expresso code to do this. This project will also have some web coding and potential for industrial interactions.

    Specific details:

    There are a number of parts to this project, first we will need to develop a method to generate potential candidate materials and their associated atomic structure from the periodic table which could serve as a replacement. Next we need to perform electronic transport calculations through simple interfaces of these structures. Finally we will insert defects such as grain boundaries in these structures to understand how these defects affect the conductivity properties. Note that we have built what we think is the largest database of materials science calculations and this project will directly extend this project.

  • The project will last for 8 to 10 weeks; preferably starting at the end of June, but we can be flexible.
  • We are also prepared to consider current Cambridge students who are planning to start an MSc/MPhil or PhD in Cambridge next academic year.
  • This placement is available to all students, whether EU or not.
  • This will be mainly supervised by Dr Jonathan Bean.
  • If interested, please contact Dr Jonathan Bean. Applications should consist of your CV and a short cover letter highlighting why this project is a good fit for you. Applications are due by 30.04.19 and interviews will be held on in May.
  • This UROP may offer an opportunity to continue into a 4th year project.

  • Insertion Date: 27 January 2020


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    Data mining of nanogap plasmonics

    Lead SupervisorsProf Jeremy J Baumberg FRS and Dr Bart DeNijs of the Cavendish Laboratory, Department of Physics
    Project Taken

    Project Description:

    Trapping light to the nanoscale using noble-metal 'plasmonics' opens up the possibility to understand how morphologies change on the few atom size scales. In this project you will analyse our huge data store taken using automated spectroscopies of scattering and Raman spectra, to understand their correlation. You will develop a new understanding of the way different shaped nanoparticles produce different light trapping, and how this changes their optical response.

  • A strong background in python programming is essential.
  • Period of the project: 8-10 weeks.
  • If interested, please contact Prof Baumberg as soon as possible.

  • Insertion Date: 24 February 2020


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    Cricket and Data Science: Why do Cricket Balls Swing?

    Lead Supervisor: Dr Sam Grimshaw,Whittle Laboratory, Department of Engineering
    Project Taken

    Project Description:

    The Whittle Laboratory and The England and Wales Cricket Board (ECB) are working together on a project to study the aerodynamics of cricket ball swing. The ECB have a large database of statistics gathered from international cricket matches which includes ball trajectories. This project aims to "mine" the data to look for correlations and patterns which will help us to understand why a cricket ball swings (and why sometimes it doesn't).

    As part of the project the student will develop a method to combine the ball trajectory information with biomechanical data enabling a new analysis of how players swing the ball, bowl different lengths and bowl quickly. We also have access to high quality video footage and if time permits the student will build on existing ball tracking software by adding a seam angle and seam wobble analysis. These are important parameters in determining whether a ball will swing or not.

    We expect that dbslice dbslice will be used as a platform to process and visualise the data and that the data analysis may require a machine learning approach.

  • The project would suit a student from any year interested in a combination of aerodynamics, data science, biomechanics and sport.
  • The 8-week project will be based at the Whittle Laboratory and has a flexible start date.
  • If interested, please contact Dr Sam Grimshaw as early as possible.

  • Insertion Date: 12 February 2020


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    Sensor Characterization and Interactive Visualization

    Lead Supervisor: Dr. Phillip Stanley-Marbell, Department of Engineering
    Project Taken

    Project Description:

    All sensor manufacturers publish datasheets that describe the technical specifications of the sensors they manufacture. These datasheets include quantitative information characterizing many important properties of sensors. An analysis of a large collection of datasheets could reveal historical trends and correlations between sensor parameters: An initial analysis suggests that there are indeed correlations between sensor power dissipation and noise parameters across a large collection of sensors from different manufacturers over the last several decades. Previous similar analyses of properties of digital integrated circuits [1] and their power dissipation and packaging properties has proven to be very influential commercially and highly cited academically.

    This UROP will build an interactive database of information for a large number of commercial sensor integrated circuits. The student will obtain the underlying data from published datasheets, building on preliminary work that has already been completed. The student will then build an interactive online tool to enable plotting and analysis of the sensor data, integrating it with a large database for other integrated circuit types [1].

    [1] P. Stanley-Marbell, V. C. Cabezas and R. P. Luijten, "Pinned to the walls - Impact of packaging and application properties on the memory and power walls," IEEE/ACM International Symposium on Low Power Electronics and Design, Fukuoka, 2011, pp. 51-56. doi: 10.1109/ISLPED.2011.5993603

  • If interested, please contact Dr. Phillip Stanley-Marbell to apply or for further information.

  • Insertion Date: 27 January 2020


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    Design and fabrication of a scalable multi-modal imaging fiducial for improved surgical interventions

    Lead Supervisor: Dr. Sarah Bohndiek and Dr. James Joseph of the Department of Physics
    Project Taken

    Project Description:

    Recent studies have demonstrated the unique potential of multi-modal imaging to enhance the diagnostic capability of medical imaging. Particularly, fusion of pre-operative MRI or X-ray CT with localised ultrasound and optical imaging during surgery is becoming increasingly important for surgical margin assessment. A major challenge in this field is the lack of robust image registration methods. While much progress has been made in software-based systems, a limitation remains the development of fiducial markers that facilitate multi-modal co-registration. One of the key requirements to overcome this challenge is to use a fiducial marker that provides contrast in all modalities. This project aims to perform a systematic investigation of contrast modifiers in MRI (altering T1 and T2 relaxation times), CT (affecting Hounsfeld units), ultrasound (acoustic reflectors) and optical imaging (absorbers and scatterers). These contrast modifiers will be incorporated into electrospun fibres of diameters to create a multi-modal imaging fiducial.

    This project will be based in the VISION laboratory.

  • Interest in medical physics and programming experience for image analysis, for example in Python or Matlab is essential and prior experience in a medical imaging research project would be useful.
  • The project duration is expected to be 10 weeks.
  • If interested, please contact Dr. Sarah Bohndiek as soon as possible.

  • Insertion Date: 25 February 2020


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    Simulation of aging vision in VR

    Lead Supervisor: Dr. Rafal Matiuk, Department of Computer Science & Technology
    Project Taken

    Project Description:

    Our research group has been working on the effects of aging on human spatial and color vision. The ultimate goal is to develop methods that would adapt displayed images to account for vision deficiencies. This is to personalize graphics and displays and offer the best experience despite differences in visual performance.

    The goal of this internship is to develop a VR-based demonstrator that will simulate and visualize differences in vision across ages. The internship will involve programming Unity application and shaders.

  • The candidate must have a fundamental knowledge of computer graphics (at least at the level of 1A Introduction to Graphics).
  • The candidate should have prior experience with Unity or should be willing to learn development in Unity
  • The project is planned for 8-10 weeks. The project should ideally start in June, a few days after the examinations. Other dates are also possible.
  • If interested, please contact Dr. Rafal Matiuk as soon as possible.

  • Insertion Date: 9 March 2020


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    Visual loss function for deep learning

    Lead Supervisor: Dr. Rafal Matiuk, Department of Computer Science & Technology
    Project Taken

    Project Description:

    Deep neural networks have shown remarkable performance in various image processing and reconstruction tasks, such as deblurring, denoising, or single-image super-resolution. However, those methods often employ simple arithmetic loss functions (L2, L1), which do not account for the perception of differences and produce images of lower visual quality.

    The goal of this internship is to help in the development of differentiable perceptual loss functions for training image-to-image translation networks. The work will involve implementing visual difference metrics in PyTorch/TensorFlow.

  • The experience with training deep-neural-networks, ideally for image-to-image translation, is highly desirable.
  • The candidate should be familiar with PyTorch/TensorFlow.
  • The project is planned for 8-10 weeks.
  • If interested, please contact Dr. Rafal Matiuk as soon as possible.

  • Insertion Date: 9 March 2020


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    Robotic Manipulation Platform Development

    Lead Supervisor: Dr. Fumiya Iida, Department of Engineering
    Project Taken

    PROJECT CANCELLED:

    Manipulation of a large variety of objects are still significant challenges for robots. This project aims to develop an integrated robotic manipulator to demonstrate robotic manipulation of large variety of objects. By using a co-working robotic arm platform, the student is expected to integrate mechanical, electrical and software components to demonstrate tasks.

    The project will be based in the Bio-Inspired Robotics Lab.

  • The student working on this project needs to be able to program python and learn how to use physical robot platforms. The practical skills of computer vision and machine learning are also essential.
  • The project can be continued as a 4th year student project.
  • If interested, please contact Dr. Fumiya Iida, as early as possible.

  • Insertion Date: 3 February 2020


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    Open source modular robot development

    Lead Supervisor: Dr. Fumiya Iida, Department of Engineering
    Project Taken

    PROJECT CANCELLED:

    This project develops a modular robot system and simulation models for the purpose of effective and efficient student research and education. The system consists of commercial sensor/motor components, along with some 3D printed parts, which can be quickly constructed into simple robotic arms or legged robots. By building and experimenting with these systems, the students should be able to learn the fundamentals of robot design, control, and simulation, both theoretically and practically.

    The project will be based in the Bio-Inspired Robotics Lab.

  • The student working on this project needs to work with basic matlab scripts, CAD designs, 3D printing. Technical writing for instructions and reporting is also necessary.
  • The project could be continued as a 4th year student project.
  • This project will be co-supervised by Rick Hyde from Mathworks.
  • If interested, please contact Dr. Fumiya Iida, as early as possible.

  • Insertion Date: 3 February 2020


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    Compacting strings with a generational garbage collector

    Lead Supervisor: Jeremy Yallop, Department of Computer Science & Technology
    Project Taken

    Project Description:

    The run-time representation of strings in a programming language can have a significant effect on the performance of programs. Flat array representations (currently used in OCaml) provide fast indexing but slow concatenation. Contrariwise, more structured string representations such as ropes provide fast concatenation but slower indexing.

    This project will explore a representation that combines the best of both worlds, where strings are initially constructed as ropes, then collapsed into a flat representation during a garbage collector cycle (e.g. when strings are promoted from the minor heap to the major heap).

    Background reading:

  • The chapters "Memory Representation of Values" and "Understanding the Garbage Collector" of Real World OCaml
  • The article "Ropes: An alternative to strings" (H. Boehm, R. Atkinson, M. Plass, 1995)


  • Since the project involves modifying the OCaml compiler and run-time system, you'll need strong OCaml and C programming skills, an understanding of compilers and an interest in garbage collection.
  • The project is expected to run for 8-10 weeks.
  • If interested, please contact Jeremy Yallop as soon as possible.

  • Insertion Date: 6 March 2020


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    Turing patterns in bacteriophage-bacteria communities and their role in ecosystem robustness

    Lead Supervisor: Dr. Diana Fusco, Department of Physics
    Project Taken

    Project Description:

    The formation of spatial patterns is a key research area in physical biology, with applications ranging from tissue development to ecology. In 1952, Alan Turing proposed a way in which such patterns can spontaneously emerge in reaction-diffusion systems where spatial instabilities are amplified around an otherwise stable equilibrium. One area in which such pattern formation plays a crucial role is in the dynamics of interacting populations, such as predator-prey systems. It has been shown that a necessary condition to observe Turing patterns in Lotka-Volterra predator-prey models is the presence of a cross-diffusion term, so that the dispersal of the predator depends on the local prey density.

    Interestingly, certain types of viral infections fall into this category. Bacteriophage, which is a virus that infects bacteria, exhibits a diffusion coefficient that depends on bacterial density, since its dispersal is hindered by the presence of the bacterial host. As a consequence, the phage-bacteria system naturally satisfies the necessary conditions to observe Turing patterns. The aims of this project are: (i) to determine whether and under what conditions Turing patterns can occur in the phage-bacteria system, and (ii) evaluate how such patterns increase the robustness of the ecosystem by widening the parameter range in which both species co-exist in comparison to non-spatial settings.

    This project, computational in nature, will involve using Matlab, Python or another suitable programming language to numerically solve the reaction-diffusion model describing the phage-bacteria system and to identify the parameter regions that exhibit spatial patterns. The nature of the work provides a great opportunity to develop programming skills, a theoretical understanding of reaction-diffusion models and dynamical systems, and viral infection models.

    The project will be in the Fusco lab.

  • Programming experience is essential (Matlab, Python or similar), strong mathematical background and an interest in biological physics.
  • This UROP project may NOT be submitted as a Long Vacation Project in lieu of one Part II item of Further Work or one Part III Minor Topic. Note also that Department of Physics does not allow long vacation work to be used as the basis of a Part III Project.
  • The Cavendish Lab has agreed to secure the funds for a Long Vacation Bursary to cover the costs of this project. This will offer up to 10 weeks' standard stipend.
  • If interested, please contact Dr. Diana Fusco as soon as possible.

  • Insertion Date: 9 March 2020


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    Machine learning for identifying rhythms in biological data

    Lead Supervisor: Dr. Ramji Venkataramanan, Department of Engineering
    Project Taken

    Project Description:

    Circadian (24h) rhythms are ubiquitous in nature, and control most processes in mammals including body temperature, blood pressure, and locomotor activity. Moreover, the clock system drives 24h rhythms in gene and protein expression in tissues within the organism. In order to study these rhythms, time series datasets are constructed by measuring expression at regular intervals over a 24h cycle. While such time series are easily obtained from model organisms in the lab, performing such time course experiments on humans presents practical and ethical difficulties.

    One possible solution to this problem is to collect single measurements from a population and then reconstruct the time courses from sufficiently many measurements. Such population data are already available in multiple public databases, but lack information on the measurement time of each sample. This project will address the problem of inferring time labels from such data to identify circadian rhythms in genes of humans and other mammals.

    In particular, we will compare recently proposed techniques for this problem (see [1],[2]) with more interpretable approaches based on sparse principal components analysis [3]. The student will work with publicly available circadian time series datasets and investigate different approaches to infer rhythms in gene expressions.

    References:

    1. Leng, N. et al. Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments. Nature Methods 12, pp. 947-950 (2015).

    2. Anafi, R. C. et al.. CYCLOPS reveals human transcriptional rhythms in health and disease. Proceedings of the National Academy of Sciences 114, pp. 5312--5317 (2017).

    3. Sparse Principal Component Analysis, Journal of Computational and Graphical Statistics, Vol. 15, No. 2, Pages 265-286 (2006)

  • This project will be co-supervised by Dr Bharath Ananthasubramaniam at the Institute for Theoretical Biology in Berlin.
  • The candidate will have familiarity with basic machine learning and inference algorithms (e.g., at the level of the 3F8 module in the Department of Engineering.) Basic knowledge of biology is a plus, but not essential.
  • The candidate will have programming experience in a scripting language such as Python or Julia. Ability to work with large datasets using standard tools is desirable.
  • The project is planned for 8-9 weeks, exact dates are flexible.
  • If interested, please contact Dr. Ramji Venkataramanan as soon as possible.

  • Insertion Date: 9 March 2020


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    Development of Online STEM Teaching Materials

    Lead Supervisor: Dr. Dongfang Liang, Department of Engineering
    Project Taken

    Project Description:

    E-learning is becoming increasing popular worldwide. It has the advantage of having a multimedia learning environment and being extremely flexible. This project will focus on the online teaching of STEM (Science, Technology, Engineering and Mathematics) subjects to school students. The project activities involve the development of effective teaching materials and syllabi, the preparation of assignments and test, as well as reviewing existing contents and proposing academic standards. An online teaching platform will be used to produce online lessons and activities, with their effectiveness compared and evaluated.

  • A good understanding of the UK national curriculum and good command of English are essential.
  • The project will run for 8 weeks.
  • The project is being co-supervised with Dr. Jack Chen from Cam Dragon Co Ltd.
  • The work has the potential to be continued as a 4th year project.
  • If interested, please contact Dr. Dongfang Liang as soon as possible.

  • Insertion Date: 9 March 2020


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    Unconventional Fermi surfaces in insulators

    Lead Supervisor: Suchitra Sebastian, Department of Physics
    Project Taken

    Project Withdrawn:

    The project will involve the study of Fermi surfaces in exotic phases of quantum matter using the tool of quantum oscillations under conditions of low temperatures and high magnetic fields. An experiment will be designed to enable the study of quantum oscillations at high magnetic fields using electrical transport and magnetic torque measurements. Studies will be performed involving the tuning of magnetic fields and tilt angle, thus enabling the evolution of the Fermi surface to be tracked.

  • The cadidate will need skills in independence, resourcefulness, good communication and teamwork.
  • The project will be 10 weeks long.
  • This UROP project may NOT be submitted as a Long Vacation Project in lieu of one Part II item of Further Work or one Part III Minor Topic.
  • This project will be co-supervised with Alex Eaton from the Department of Physics.
  • If interested, please contact Suchitra Sebastian as soon as possible.

  • Insertion Date: 9 March 2020


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    Cavenish Scientific Computing

    Lead Supervisor: Paul Alexander and Malcolm Longair, Cavendish Laboratory, Department of Physics
    Project Taken

    Project Description:

    This project would investigate the computing techniques and programs used in the 1950s-70s as part of the Cavendish Lab's research, with a focus on Radio Astronomy. Sir Martin Ryle credited David Wheeler's independent discovery of the Fast Fourier Transform with enabling him to create telescopes such as the One-Mile. What other programs or routines were written for the EDSAC, EDSAC 2 and TITAN computers, and how did they enable Radio Astronomy research? We know code was written for contour plots for mapping sky brightness, and for control systems programming for the One-Mile Telescope. Can we recover and analyse the code, or find other examples? This project would also reveal the contribution women made to scientific computing, as programmers. The project would require archival work using the Department of Computer Science archives, plus examination of the Radio Astronomy Group theses and papers.

    This project will be based in the Battcock Centre for Experimental Astrophysics.

  • Desirable criteria: an interest in radio astronomy techniques, a basic understanding of programming, and an interest in archival work.
  • The project will ideally start before the end of June for 10 weeks.
  • If interested, please contact Verity Allan before 31 March 2020.

  • Insertion Date: 2 March 2020


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    Researching the Cavendish Collection of Historical Scientific Instruments: the role of the Research Councils and the EPSRC since the 1950s

    Lead Supervisor: Professor Malcolm Longair, Cavendish Laboratory, Department of Physics
    Project Taken

    Project Description:

    Description In 2022, we will move the Cavendish Collection of Historic Scientific Instruments to the new Cavendish Laboratory. The project consists of researching the origins of the instruments in the collection, what they did and why they are important historically. The emphasis will be upon the period from 1950s to the present day during which time the Laboratory has been successful in winning research council grants. This information is available for some of the most well-known instruments, but most of the collection needs more detailed study and analysis. In particular, the recent history, the era of the research councils, is poorly documented and requires considerable research.

    The outcome of this project will play a key role in determining which of the 900+ instruments should go on display and the information to be provided to visitors. There will be the opportunity to study some little known but important instruments and developing engaging stories about them. Unlike the present display, the new exhibition will include many more diverse aspects of the activities in the Laboratory. The role of women, assistant staff, unsung heroes, spin-off companies, the changing pattern of science education and the application of research will be highlighted. There will also be the opportunity to help develop the nature of the layouts of the displays in the new areas, which will be a prominent part of the major displays in the new Cavendish Laboratory.

    The contents of the exhibition will be a major part of our outreach programme to young people and the interested public, as well as being of prime interest for historians of physics. The project will be supervised by Professor Malcolm Longair and Dr. Isobel Falconer, who are both experts on the History of the Laboratory. Because of the diversity of the EPSRC funded projects, it is a major intellectual challenge to catalogue and evaluate the importance of these research funded projects. The student will gain in depth knowledge of the process of research and discovery in physics. Full acknowledgement will be made of the key role of the research councils in enabling the advance of physics research in a rigorous but appealing fashion. Modern technologies using smart phones will be used to replace long explanatory captions. The aim is to create a continuous narrative of how physics evolved in so many different ways.

  • The student should have an excellent grasp of experimental and theoretical physics and an interest in historic instruments and their role in discovery in Physics.
  • The project will preferably begin in the second week of August 2020 and run for 8 weeks. There is some flexibility in the dates.
  • We expect this will be an excellent educational project for an enthusiastic student. We would probably recommend a more traditional project in the fourth year, unless specialising in History and Philosophy of Science.
  • This project will be co-supervised by Dr. Isobel Falconer, Department of Mathematics, University of St. Andrews. Isobel is an expert on the Cavendish Collection and will spend some time with us during the period of the project.
  • If interested, please contact Professor Malcolm Longair as soon as possible.
  • This project taking place will be subject to securing EPSRC funding.

  • Insertion Date: 3 March 2020


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    Modelling single-ion behaviour in frustrated magnets and quantum spin liquids

    Lead Supervisor: Dr. Claudio Castelnovo, Cavendish Laboratory, Department of Physics
    Project Taken

    Project Description:

    Disorder and distortions have often been regarded as a nuisance that one ought reduce as much as possible. Notwithstanding their omnipresence in real materials, recent work has shown that they can be a resource to tailor the properties of materials in new and exciting ways. In frustrated magnetism, defects can induce new degrees of freedom, stabilise/induce new phases of matter, and -- perhaps even more surprisingly -- they can enhance quantum fluctuations, providing a new and unexpected route to investigate quantum spin liquid behaviour. This project aims to lay the foundations of a systematic investigation of the effects of disorder in magnetic materials by setting up point-charge Crystal Electric Field calculations [*] to understand the single-ion response to distortions, its change in magnetic behaviour, and the relevant energy scales involved. The results will seed many body investigations of the collective behaviour of these systems (this part however will likely extending beyond the realistic scope of the summer bursary).

    [*] for an example of this type of calculations, see Sec.C in the Supplementary Information of DOI: 10.1038/NMAT3924, and references therein.

  • The project is open to second and third year students. A strong theoretical inclination is required, with familiarity (or willingness and ability to familiarise) with quantum mechanical / second quantisation notation and point group symmetries.
  • If interested, please contact Dr. Claudio Castelnovo as soon as possible.

  • Insertion Date: 24 February 2020

    Automatic Recognition of Facial Expressions with Deep Learning Approaches

    Lead Supervisor: Dr Hatice Gunes, Department of Computer Science & Technology
    Project Taken

    Project Description:

    The recognition of facial expressions from image sequences is fundamental in various applications including social robotics, human-computer interaction and healthcare. A key problem for dynamic facial expression analysis is to convert the input sequence into a useful representation. Representations learnt from data are expected to achieve high performance without requiring domain expertise. But representations used for facial expression recognition usually contain expression information along with other variations such as ethnicity, gender, illumination etc.

    The project will focus on end-to-end deep learning, and implement and compare the most recent methods in the area including disentangled representation learning based on Variational Autoencoders, with the aim of novel extensions and/or new insights for new machine learning models. Extensive experiments will be conducted on publicly available benchmark datasets.

  • The ideal candidate should have good programming skills, preferably in Python. Knowledge and some level of experience with deep learning are also needed. Basic knowledge of computer vision is a plus.
  • The project is planned for 10 weeks, exact dates are flexible.
  • If interested, please contact Dr Hatice Gunes.

  • Insertion Date: 11 March 2020


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    Reactive Transport Modelling of fluid flow and chemical evolution in the oceanic crust

    Lead Supervisor: Dr. Alexandra Turchyn, University Reader in Biogeochemistry, Department of Earth Sciences
    Project Taken

     NERC funded project

    Project Description:

    Oceanic crust is made in long chains of volcanoes on the bottom of the ocean floor, creating mid ocean ridges and helping drive plate tectonics. During the formation of new oceanic crust, seawater interacts with the new rock at a range of temperatures from those at the ocean floor (~2-4DegC) to near the critical point for water (300-400DegC) as much as 4-5km below the ocean floor. Through this interaction, termed hydrothermal circulation, the new rocks in the oceanic crust are altered and the seawater evolves its chemical composition, losing many ions and gaining others. When seawater emerges as hydrothermal fluid in vents near the surface, it has an entirely different chemical composition to that which it started with. This process is believed to be one of the key processes influencing the chemistry of the ocean over geological time.

    The chemical evolution of seawater in hydrothermal systems is also important as it leads to the sequestration of carbon within the oceanic crust through carbonate mineral and vein formation. Often a record of this water-rock interaction is recorded in the minerals that are found in ancient oceanic crust. What we can see is that the chemistry of these minerals does change over time, telling us that either the evolution of fluid through the crust has changed, or the chemistry of the ocean has changed, or both. Some outstanding questions include, when the boundary conditions change (that is the chemistry in the ocean), how does this influence water rock interaction in the oceanic crust? How does this influence the ability of the crust to store carbon? How does it influence the chemistry of water in hydrothermal systems?

    This project will explore these ideas by using a chemically enabled reactive transport modelling software, CrunchTope. The student will learn from group members how to operate and code in CrunchTope and then will use this software to explore the evolution of hydrothermal chemistry in the modern ocean, with known parameters such as modern-day ocean chemistry and the chemistry of hydrothermal vent fluids. One objective is to be able to match the range of hydrothermal vent chemistry as a function of the type of oceanic crust. A second objective is to use the model to predict and calculate how much carbon might be stored in the oceanic crust as a function of the balance of ion exchange that occurs during water-rock interaction. Once the model has been verified for the present day, the student will explore what happens when the chemistry of the ocean changes and how this then influences both the chemistry of vent fluids, the nature of water-rock interaction and the storage of carbon in the oceanic crust.

    As this project will be NERC funded the sucessful student must meet all of the following criteria:

  • Be studying for a degree in a quantitative discipline outside of NERCs scientific remit (e.g. mathematics, statistics, computing, engineering, physics is acceptable)
  • Be applying for a placement in a different department to their undergraduate degree
  • Be undertaking their first degree studies (or integrated Masters)
  • Be expected to obtain a first or upper second class UK honours degree or equivalent
  • Be eligible for subsequent NERC PhD funding (UK, EU or right to remain in the UK)

  • Preference for students who are enthusiastic, curious, and willing to think outside the box. Matlab/Python experience a bonus, some fluid dynamics would be helpful.
  • The project can be carried out fully remotely for a period of 6 weeks.
  • The research group is currently meeting via zoom/teams/skype weekly for discussions on the project objectives and progress.
  • To apply please send a CV to the lead supervisor Dr. Alexandra Turchyn as soon as possible.

  • Insertion Date: 8 June 2020


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    Propulsion and Power

    Lead Supervisor: Dr. Sam Grimshaw, Department of Engineering
    Project Taken

     European Union citizens ONLY EPSRC criteria may apply CLICK HERE for criteria

    Project Description:

    The National Centre for Propulsion and Power will be at the heart of the new Whittle Laboratory. It will contain a unique system of wind tunnels and rotating rigs which will enable rapid technology development for a low carbon future. The team at the Whittle Laboratory is currently engaged in the detailed design of the test facilities. This involves understanding trade-offs between a variety of factors including the test conditions that can be achieved, physical space available, selection of compressors to drive the system, capital costs and operating costs.

    The student undertaking this project will first study the system level design with low order modelling and second set up and run CFD simulations of an important subsystem. The system level study will build on an existing model by updating aerodynamic and cost assumptions. This parameterised model will then be coupled with optimisation methods to explore the design space and help to quantify the trade-offs. The CFD simulations will investigate the effect of various parameters on the performance of an open-jet wind tunnel configuration.

  • The project would suit a 3rd year engineering student going into 4th year who is interested in aerodynamics, modelling and optimisation problems.
  • The 8-week project will be run remotely with supervision via Microsoft Teams.
  • The start date is flexible.
  • This project is funded by the EPSRC Vacation Budget and eligibility restrictions apply.
  • Please contact Dr. Sam Grimshaw, to apply or for further information.

  • Insertion Date: 17 June 2020


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    Dynamic balancing of feedback and feedforward in robotics

    Lead Supervisor: Dr. Fulvio Forni, Department of Engineering
    Project Taken

    Project Description:

    High-gain feedback is effective in motion control. Aggressive feedback dominates nonlinearities and unmodeled dynamics, thus guarantees a well regulated behavior in closed loop. But high-gain feedback is energetically expensive and fragile to sensor noise and faults. An alternative approach is provided by humans, which reach good motion control without aggressive feedback, by combining low-gain feedback and feedforward action in a clever way. The purpose of the project is to investigate this bio-inspired approach in motion control, starting from simple nonlinear actuators, then moving towards more complicated robotic manipulators. The aim of the project is to study algorithms that adapt the strength of the feedback action while learning the feedforward action. The goal is to achieve good motion accuracy without aggressive feedback. This is particularly important for energy-efficient motion and safe human-machine interaction.

    The project will combine classical feedback control with feedforward adaptive action for robotics, possibly implemented via neural networks. The project is part of a wider research topic which combines classical control with novel learning/adaptation algorithms to enable continuous learning while improving the effectiveness of the feedback action. This should open new directions in soft robotics and neuroscience.

    Further readings: C. Della Santina et al., "Controlling Soft Robots: Balancing Feedback and Feedforward Elements," in IEEE Robotics & Automation Magazine, vol. 24, no. 3, pp. 75-83, Sept. 2017. doi: 10.1109/MRA.2016.2636360

  • The project will involve modeling, simulations, and coding in Matlab. This would be suitable for a student in the IB or IIA.
  • The expected duration is 10 weeks. The project may start after mid June and ideally early July 2020.
  • Due to current COVID pandemic, the project will be supervised remotely. Candidates must have a computer and reliable access to internet.
  • Please contact Dr. Fulvio Forni to apply or for further information.

  • Insertion Date: 18 May 2020


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    Reconstructing westerly winds using Antarctic ice cores

    Lead Supervisor: Dr. Liz Thomas, British Antarctic Survey
    Project Taken

     NERC funded project

    Project Description:

    Winds around the Southern Ocean play a key role in driving the exchange of heat and carbon dioxide between the oceans and the atmosphere. In recent decades, the circumpolar wind belt has increased in strength and has shifted towards the Antarctic continent, constituting one of the strongest climatic trends in the Southern Hemisphere over the last decades. These changes have been linked as drivers of the widespread warming observed on Antarctic Peninsula (AP) and West Antarctica (WA) and as the mechanism behind the enhanced upwelling of deep and relatively warm, carbon-rich, oceanic water. The upwelling of this circumpolar deep water has shown to promote the accelerated melting and thinning at the base of the ice shelves, contributing to sea level rise and threatening the stability of floating ice shelves along the coastline of the Amundsen-Bellingshausen Seas.

    To understand how recent changes in wind strength and atmospheric circulation have impacted the regional climate, it is necessary to study how winds have evolved in the past. The lack of reliable long-term observational wind records in the AP and WA, hinders the ability to place the recent observed changes in the context of a longer time frame.

    Ice cores yield valuable climatic information through the use of proxy records. Windblown particulate matter trapped in Antarctic ice cores provides unique information about changes in the regional wind strength and atmospheric circulation. Meltwater from several Antarctic ice cores has been filtered and those filters imaged using a Scanning Electron Microscope (SEM). These images contain a vast amount of data relating to westerly winds. The analysis of this data requires visual scanning of the SEM images to determine the abundance, diversity ad size of different targeted particulate matter.

    This project aims to produce a physical characterization of windblown particle matter present in Antarctic ice cores. For this, the student will work analysing SEM images to create a complete dataset of targeted particle matter. Additionally, the student will help in the processing and chemical analyses of Antarctic ice core samples at the British Antarctic Survey.

    Links to relevant supporting information:

      Allen, C , Thomas, E R. , Blagbrough, H , Tetzner, D, Warren, RA., Ludlow, EC., Bracegirdle, T J. . (2020) Preliminary Evidence for the Role Played by South Westerly Wind Strength on the Marine Diatom Content of an Antarctic Peninsula Ice Core (1980–2010) Geosciences, 10. 10.3390/geosciences10030087

    As this project will be NERC funded the sucessful student must meet all of the following criteria:

  • Be studying for a degree in a quantitative discipline outside of NERCs scientific remit (e.g. mathematics, statistics, computing, engineering, physics is acceptable)
  • Be applying for a placement in a different department to their undergraduate degree
  • Be undertaking their first degree studies (or integrated Masters)
  • Be expected to obtain a first or upper second class UK honours degree or equivalent
  • Be eligible for subsequent NERC PhD funding (UK, EU or right to remain in the UK)

  • Candidates must be aware that this project will potentially involve working inside a cold chamber (-23C) to process ice core samples. Thus, we expect candidates willing to work under cold temperature conditions. The British Antarctic Survey will provide full training and appropriate clothing.
  • This will be for a six week period.
  • There is good potential to conduct this project remotely. The core of this project is the analysis of digital SEM images that have already been acquired. Thus this project can be easily switched to be carried out remotely as the student can be trained online through videoconferences and the images shared via dropbox or one drive.
  • To apply please send a CV to the lead supervisor Dr. Liz Thomas as soon as possible.

  • Insertion Date: 17 June 2020


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    BELOW THIS LINE IS NOT VISIBLE ON THE WEB SITE So copy and paste the text and hyperlinks between the lines and use as template DELETE WORDS BETWEEN asterisks.** __________________________________________________________________________ PROJECT TAKEN IMAGES Project Taken

    ++++++++++ DUMMY PROJECT DESCRIPTION +++++++++++++

    NAME OF THE PROJECT

    Contact:Lead Supervisor: Dr.Zuess Secret Lab
    Project Available

    Project Description:

    Setting the world to rights.


    Please apply to Contact/Lead Supervisor.

    This project will be co-supervised by Professor Bob Dillon Cavendish Lab

    Working 10 weeks over the summer

    Insertion Date: 1 February 2016


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