Announcing 2024 Summer Internships for Leicester Undergraduates

Applications are open for the Summer Undergraduate Research Experience (SURE2024) scheme for 3rd and 4th year Leicester undergraduates.

The SURE programme provides paid opportunities for capable undergraduates to get a flavour of what it is like to work at the cutting-edge of research in the School of Physics and Astronomy. 

We will host 4-5 Leicester undergraduates (3rd or 4th year students) for paid internships, working on Central Campus or at Space Park Leicester. Internships will be for a maximum of six weeks (35 hrs/week) and can be undertaken at any point between June 1st and August 31st, subject to negotiation with the proposed supervision team. You will be expected to present the results of your internship to the School at the end of August and to provide reports to your supervisors, as appropriate. 

We particularly encourage applications from students who have not benefitted from an internship in the past and are yet to secure a graduate position, for whom an internship will likely be of greatest benefit for their long-term career ambitions. 

Application Process

To make an application, please send an email to with the following two attachments: 

  • A one-page curriculum vitae as a PDF. This should summarise your qualifications, employment history, and any relevant experience or achievements. 
  • A completed application form as a PDF (available in DOCX via Blackboard, you must be logged in to view the page). Your application must include, 
    • a selection of three selected projects from the list below; 
    • any dates between June 1st and August 31st on which you are unavailable (you may also, optionally, specify the dates during that period on which you would prefer to undertake your project); 
    • A nominated referee (this person will only be contacted for a standard Unitemps reference if you are shortlisted for a post); and 
    • a personal statement (no more than one side of A4) explaining how your existing skills and experience make you well suited to excel at your three selected projects. 

Applications will be accepted at any time before 2pm on Friday March 8th. Please do not leave it to the last minute. 

Selections will be made by a panel consisting of the SURE supervisors below, with announcements by early April 2023. The criteria for selection include: 

  • Progress and grades during your degree to date. 
  • Suitability for the chosen research project, including appropriate computational or experimental skills. 
  • Context of the application such as how this may benefit future career ambitions, improving access to underrepresented groups, or topical decisions for PhD research or further employment. 

Please address any queries to

Project Descriptions

Please continue to check back as more projects may be added to the list below. 

BRI24: New Analytical Microscopy Techniques at the University of Leicester 
CAS24: Discovering New Jupiters Around Low Mass Stars With the Next Generation Transit Survey 
EYL24: Using Machine Learning and AI to Investigate the X-ray Sky 
HAL24: The Elemental Composition of Mercury’s Crust 
HUM24: Investigating Greenhouse Gas Concentrations Over the UK Using Ground-Based Remote Sensing 
JOY24: Using Artificial Intelligence to Study the Martian Ionosphere  
POV24: Are Clouds Fractal? 
SAR24: Modelling Lunar Dust Particle Trajectories Following Moon Rover Traverses

BRI24: New Analytical Microscopy Techniques at the University of Leicester 

Supervisor team: Prof John Bridges, Dr Leon Hicks 
Categories: Experimental 
Location: Space Park Leicester 

Planetary materials research at the University of Leicester involves analysis, with a wide range of microscopy-based analytical techniques, of meteorites and material returned from missions to asteroids and comets, the Moon, and ultimately Mars. Every year we hold an RAS-funded planetary materials SURE internship to help develop some aspect of our research.  

This year the student will be trained in the use of electron microscopes and in particular aspects of a newly installed Zeiss microscope system (housed in the Advanced Microscopy Facility) which allows correlated Computer Tomography, focused ion beam, femtosecond laser and high-resolution electron microscopy. This ‘Hercules’ system can provide highly accurate compositional and textural analyses of planetary materials, combining datasets in a unique way. The femtosecond laser and ion beam can also potentially be used to mill and extract microscopic components for space instrumentation. 

This internship will involve understanding the theory and analyses of selected planetary materials and other material to help build our capability with this instrumental technique – which is unique in the UK and Europe. It is suitable for a student interested in an interdisciplinary, experimental space science project. 

CAS24: Discovering New Jupiters Around Low Mass Stars with the Next Generation Transit Survey 

Supervisor team: Dr Sarah Casewell
Categories: Data Analysis 
Location: Campus 

The Next Generation Transit Survey (NGTS) is an array of 12 independently mounted telescopes located at Cerro Paranal in Chile. We monitor stars every night searching for dips in lightcurves, indicating a planet has passed in front of a star. As the project generates lightcurves for millions of stars, we use a citizen science project – PlanetHunters NGTS – to help check and validate our planet discoveries. That dataset contains all of the lightcurves rejected because they have a visible secondary eclipse (when the planet moves behind the star). While this would usually indicate a binary system and not a planetary system, if the primary star is physically small and cool (an M dwarf), then the secondary eclipse could be due to a Jupiter-sized planet or brown dwarf. 

In this project, the student will help search through the Planethunters data for M dwarf stars, examining their lightcurves, and fitting models to the best candidates to determine the likely planet parameters. The project involves data analysis and programming using the Python programming language. As a part of the Centre for Exoplanet Research, the student will work with the NGTS team and attending the weekly group meetings during the project. 

EYL24: Using Machine Learning and AI to Investigate the X-Ray Sky 

Supervisor team: Dr Rob Eyles-Ferris, Dr Phil Evans 
Categories: Data Analysis, Computational 
Location: Campus 

The Living Swift-XRT Point Source (LSXPS) catalogue is a unique resource – a catalogue of all X-ray point sources observed by Swift from its launch nearly 20 years ago and continuously updated in real time. LSXPS and its transient detector have already made valuable discoveries, such as Swift J0230, a unique object where a star is repeatedly torn apart by a supermassive black hole. However, the nature of many of the hundreds of thousands of sources in LSXPS is still unknown and there could be many unique objects waiting to be discovered. 

In this project, we will attempt to classify sources in LSXPS using machine learning methods. From the catalogue, we will create a training set of objects whose nature is known via, for instance, cross correlation with other catalogues of specific types of objects or manual inspection. We will then develop machine learning models and train them on this dataset before applying them and evaluating their performance. The results of this work could be used to identify both historical anomalies as well as spot new and unprecedented events in real time. 

HAL24: The Elemental Composition of Mercury’s Crust 

Supervisor team: Dr Graeme Hall, Prof John Bridges, Dr Adrian Martindale, Dr Julia Cartwright 
Categories: Data Analysis 
Location: Space Park Leicester 

BepiColombo, the joint European Space Agency (ESA) and Japanese Space Agency (JAXA) mission to Mercury, is now approximately two years away from first light. The Mercury Imaging X-ray Spectrometer (MIXS) instrument developed and built at Leicester offers a unique opportunity to study the elemental composition of Mercury’s crust in unprecedented detail. A novel instrument, such as this, requires new and refined analysis methods and techniques to maximise the science return from the instrument.  

The focus of this SURE internship will be to investigate the variation in elemental composition, with location and depth, using simulations of surface impacts on Mercury. Data obtained from the simulations can be correlated to existing data from the MESSENGER mission to help understand the pre-impact origin of material in crater structures. Techniques developed in this project will be particularly useful when combined with the imaging capability of MIXS, once data collection begins in 2026. The project will be focused on computational simulations and data analysis, including work on the High-Performance Computing cluster, ALICE, and planetary map analysis in ArcGIS. 

HUM24: Investigating Greenhouse Gas Concentrations Over the UK Using Ground-Based Remote Sensing 

Supervisor team: Dr Neil Humpage, Dr Robert Parker 
Categories: Data analysis, with experimental option 
Location: Space Park Leicester 

Emissions of the greenhouse gases carbon dioxide (CO2) and methane (CH4), as a result of human activities, have been identified as the primary drivers of climate change. In response, the UK government has committed to achieving net zero carbon emissions by 2050, with a 78% reduction in greenhouse gas (GHG) emissions by 2035. Achieving this requires robust monitoring of atmospheric CO2 and CH4 concentrations to accurately quantify the sources and sinks of these gases, and to track progress towards the UK’s GHG emissions reduction goals. The National Centre for Earth Observation is currently setting up a new, state-of-the-art, nationwide network of ground-based remote sensing instruments that will monitor GHG concentrations over the UK, called GEMINI-UK. Once established, we expect that data from GEMINI-UK will play an important role in verifying UK GHG emissions. 

The primary aim of this project is to analyse two years of existing GHG concentration data taken at three locations across London for the DARE-UK project, using the same measurement systems that will form the new GEMINI-UK network. By looking at both long-term trends and daily variations in the concentrations of CO2, CH4, and other gases, we can investigate the emission sources and other physical processes that drive changes in the abundance of GHGs in the atmosphere. A secondary aim will be to provide a first look at new data from the GEMINI-UK network, which we expect to begin coming online from Spring 2024, and (if the student is interested in gaining practical fieldwork experience) to assist in setting up and testing the GEMINI-UK instrumentation prior to deployment. 

JOY24: Using Artificial Intelligence to Study the Martian Ionosphere  

Supervisor Team: Dr Simon Joyce, Dr Katerina Stergiopoulou, Prof Mark Lester 
Categories: Data Analysis 
Location: Campus 

New methods for data analysis using Artificial Intelligence (AI) and Data Mining (DM) are showing great promise in many areas of research and industry, from biomedical applications to driverless cars. In this project, the student will use a type of AI called a Neural Net to study a large database of images collected by the Mars Express satellite. A set of Python programs have been developed to create and train a Neural Net. This project will apply it to a set of 1.8 million ionogram images, and evaluate its capabilities. An important part of the project will be to develop the program further, so that it has the capability to recognise more features in the data, such as cyclotron lines which can be used to measure the local magnetic field strength. The end goal of the project is to discover the underlying patterns in the data and quantify how each variable affects the ionosphere. 

The Mars Express spacecraft has been orbiting Mars for 20 years, sending back a large amount of data. The Martian ionosphere, formed by the photoionization of its neutral atmosphere due to incident solar radiation, is highly variable. The ionospheric variability can be attributed to various factors such as the upstream solar wind conditions, the solar cycle, seasonal variations as well as to the crustal magnetic fields, which are magnetic patches sporadically distributed on the surface of the planet. By applying AI methods to this large database, we aim to gain new insight into the long-term trends and identify the effects of all the factors influencing the ionosphere. This project will suit a student with have an interest in planetary science, programming and AI. No previous experience with AI is required, but a basic knowledge of Python would be beneficial. 

POV24: Are Clouds Fractal? 

Supervisor Team: Dr Adam Povey, Dr Kamil Mroz 
Categories: Data Analysis 
Location: Space Park Leicester 

Clouds are ubiquitous on the Earth, covering about two-thirds of the planet at any given moment. They have numerous and conflicting impacts on climate by reflecting or absorbing solar and thermal radiation. Changes in the behaviour of clouds due to human activity is a major source of uncertainty in predictions of future climate. A cloud is smaller than the typical length scale of a pixel in a climate model, such that they must be represented by approximations rather than explicit physics. Climate models, therefore, make various assumptions about the shape, size, and evolution of clouds. 

This student will use laser and radio ranging data from satellites and ground-sites to identify the vertical extent of clouds in a variety of environments. From that mask, the fractal dimension clouds will be estimated and compared to previous results. This may be used to assess the accuracy of recent climate modelling. Data analysis will be performed in Python and, though no prior coding experience is necessary, it would be beneficial. 

SAR24: Modelling Lunar Dust Particle Trajectories Following Moon Rover Traverses 

Supervisor Team: Dr Hannah Sargeant, Dr Daniel Hao 
Categories: Computational 
Location: Space Park Leicester 

Lunar dust is highly problematic. The particles are sharp and electrostatic and can interfere with radiators and various mechanisms. When rovers or astronauts move across the lunar surface, they kick-up dust clouds, and the particles then settle on different surfaces. We have been developing a simulation that models the dust particles and can be used to predict how the dust clouds will form. The simulation will ultimately be used to inform wheel fender design and rover speed limits.   

To calibrate the model, experiments were performed with lunar soils and simulants to understand their cohesive behaviour. The same experiments must be repeated in the simulation with different parameters to produce the same properties. In this project, the student will be required to familiarise themselves with the simulation software (LIGGGHTS) using resources provided. They will have access to supercomputing facilities to complete the calibration activities and verify the simulation against footage of Moon rovers. Further information on the work done to date can be found here  


  • Why are you restricting to 3rd and 4th years? The SURE programme used to be open to 3rd year students from across the UK, but the challenges of the COVID-19 pandemic meant that many missed out on the opportunity, so we wanted to give them another shot. We will endeavour to find a good balance of 3rd and 4th year students, as described on our assessment criteria above. Our 1st and 2nd year students will hopefully have the opportunity to apply to the programme in the years to come. 
  • Why only Leicester undergraduates? Following successful pilot programmes in 2021 and 2022, and to focus on supporting Leicester students, we have chosen to keep the programme to internal applicants only. 
  • Will I be required to be in Leicester over the summer? Yes, projects will be conducted in person in Summer 2024, although hybrid working arrangements are possible in consultation with the supervisor team. You would therefore be expected to be near Leicester for the 6-week duration of your internship. 
  • How will I be paid? Students will receive an allowance from which they are expected to fund their accommodation, cost of living and travel expenses. We will use the Unitemps system of temporary staff hires. You will be paid monthly in arrears, meaning that your final payment will likely be made in September. Proof of right-to-work in the UK will be required before the internship begins. 
  • Do I have to do all six weeks consecutively? No, you are able to charge a maximum of 6*35 = 210 hours for your internship via timesheets submitted to Unitemps. You can agree with your supervisors the best way to organise those hours. 
  • How much will I be paid? In previous years students have been paid using Grade 2 Spine Point 5, which is about 5% greater than the 2023 National Minimum Wage (though this is currently under review). 
  • Do you offer unpaid internships? Unpaid roles are inaccessible and unavailable to low-income students and families, and we discourage students from taking on such positions. Your work and time are valuable, so you should be reimbursed. 
  • Are there other opportunities? Possibly – contact individual tutors, advisors, and staff to see if funds are available to support internships outside of the SURE programme (e.g., through fellowships). We will advertise any opportunities as soon as we are aware of them. 

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