2024 ALP UROP vacation projects

Several undergraduate research projects will be offered within Atomic & Laser Physics, as described below. Students working on these projects will be paid the Oxford Living Wage (from April 2024 £12.49 per hour) and subject to tax and National Insurance deductions). The projects may vary in duration and the number of hours required per week.


Undergraduate research projects are available to (i) current undergraduates; and (ii) students on taught Master's courses. Preference is likely to be given to candidates who are not due to start a Ph.D. programme in 2024.

Applications are very welcome from students of universities and institutes outside Oxford.

Please note that we are only able to accept applications from candidates who do not require a visa to work in the UK. For the avoidance of doubt, EU students currently studying in the UK who have applied for Pre-Settled status are welcome to apply along with current students in the UK on a Tier 4 visa that allows vacation employment.

How to apply

To apply for these projects please complete the online Microsoft form and attach your completed application as per the instructions.

  1. Please complete all fields in the online form here
  2. Attach a single PDF document using the following format for the document name
    LAST NAME_First Name_ALP UROP Application_Name of Project Applied for.

    This document should contain the following:
  3. A statement (of fewer than 500 words) explaining why you want to do a project, describing the previous experience, and stating the research topics or projects you are interested in.

    It should clearly state the projects you are applying for. We receive a large number of applications and this will assist with the dissemination to the Project Supervisors.
  4. a one-page CV
  5. the names of two referees who may be approached for reference letters

    Candidates are advised to submit their applications by the advised closing date. Applications received after this date may be considered, but candidates should be aware that projects may already have been allocated.

    For any questions related to your application, please contact alpadmin@physics.ox.ac.uk.

Projects offered 2024:

Internship 1: 

Supervisor: Prof. Alex Lvovsky
17 June - 11 October 2024
50% FTE contract

Machine learning has made enormous progress during recent years, entering almost all spheres of technology, the economy, and our everyday lives. Machines perform comparably to, or even surpass humans in playing board and computer games, driving cars, recognizing images, reading, and comprehension. It is probably fair to say that an artificial neural network can perform better than a human in any environment it has complete knowledge of. These developments however impose growing demand on our computing capabilities, including both the size of neural networks and the processing rate. This is particularly concerning given the decline of Moore’s law.

The project is to implement artificial neural networks using optics rather than electronics. Optical neural networks would enable us to enhance both the power efficiency and speed of neural networks by several orders of magnitude. The specific aim is to develop a conceptually novel deep optics neural network system for computer vision. This system will allow an optical neural network to “see” and interpret objects directly, bypassing the processing bottleneck associated with converting an image into an electronic form. Such a system will have ultra-low latency and find applications in autonomous vehicles, remote sensing, and intelligent robotics. Closing date: 29 March 2024

Internship 2:

Supervisor: Prof. Alex Lvovsky
17 June - 11 October 2024
50% FTE contract

Rayleigh's criterion defines the minimum resolvable distance between two incoherent point sources as the diffraction-limited spot size. Enhancing the resolution beyond this limit has been a crucial outstanding problem for many years. A number of solutions have been realized; however, all of them so far relied either on near-field or nonlinear-optical probing, which makes them invasive, expensive, and not universally applicable. It would therefore be desirable to find an imaging technique that is both linear-optical and operational in the far-field regime. A recent theoretical breakthrough demonstrated that “Rayleigh’s curse” can be resolved by coherent detection of the image in certain transverse electromagnetic modes, rather than implementing the traditional imaging procedure, which consists of measuring the incoherent intensity distribution over the image plane. To date, there exist proof-of-principle experimental results demonstrating the plausibility of this approach. The objective of the project is to test this approach in a variety of settings that are relevant for practical application, and evaluate its advantages and limitations. If successful, it will result in a revolutionary imaging technology with the potential to change the faces of all fields of science and technology that involve optical imaging, including astronomy, biology, medicine, and nanotechnology, as well as the optomechanical industry. Closing date: 29 March 2024

Internship 3:

Supervisor: TBD Oxford Ion Trap group
17 June (8-week duration)
100% FTE, flexible contract

Trapped ion is one of the most advanced platforms for quantum computing, atomic clocks, and quantum networks. Our research group at Oxford is dedicated to pioneering experimental investigations aimed at advancing quantum technologies leveraging this platform. 

We are excited to offer a range of summer projects spanning electronics, optics, programming, and theory. For more information about our research and ongoing projects, please visit: https://www.physics.ox.ac.uk/research/group/ion-trap-quantum-computing. Closing date: 29 March 2024.

Internship 4:
Proton Tomography of High Energy Density Plasmas

Supervisor: Prof. Peter Norreys
Start date: 1 July 2024 (10 week duration)
100% FTE contract

Proton radiography is a widely fielded diagnostic used to measure magnetic structures in plasma. The deflection of protons with multi-MeV kinetic energy by the magnetic fields is used to infer their path-integrated field strength. In this project, the student will investigate the use of tomographic methods to lift the degeneracy inherent in these path-integrated measurements, allowing full reconstruction of spatially resolved magnetic field structures in three dimensions for the first time. The student will investigate the strengths and weaknesses of two techniques that improve the performance of tomographic reconstruction algorithms in cases with severely limited numbers of available probe beams, as is the case in laser-plasma interaction experiments where the probes are created by short, high-power laser pulse irradiation of secondary foil targets. The student will also optimise a new configuration allowing production of more proton beams from a single short laser pulse to be used in tandem with these analytical and computational advancements involving AI and machine learning methods. The method will be applied to the first measurements of the electrothermal instability, a candidate mechanism for bi-Maxwellian ion distributions in igniting plasmas.  Closing date: Friday 26th April 2024.