MPhil/PhD studentship in Data Intensive Science with the ALICE experiment at CERN

Investing in excellence: studentship opportunities

The University of Derby has an opportunity for a full-time postgraduate research studentship in Data Science areas of research in the College of Science and Engineering 

The stipend is funded at standard UKRI rates, which is £19,237 pa for 2024/25, with an expectation that STFC will increase the rate with inflation for future years. Similarly the home tuition fee is £4,786 for 2024/25.

The studentship also includes funding for fieldwork plus research training and support, of around £3,000 and £1,200 pa respectively. This money is for activities related to the studentship and is not paid directly to the student.

It will also be possible, once the studentship has started, to apply for additional STFC funding for longer term research placement (6 months+) at CERN.

Studentship funding is for 3 years and 6 months and is funded from a UKRI Science and Technology Funding Council Doctoral Training Grant (DTG). The successful applicant will receive a maintenance stipend (based on the minimum stipend defined by UKRI) and home MPhil/PhD tuition fees. In addition an annual training and conference attendance amount of £1,200 is allocated for the studentship and funds for travel to CERN are available. Students are eligible for a funded Long Term Attachment (LTA) of up to 12 months at STFC’s international research partner facilities - applications are made in the first year of the PhD.

The vacancy details are as follows: 

Purpose/objectives

The studentship is to support the STFC science programme at Derby. In this case the work with the A Large Ion Collider Experiment (ALICE) collaboration at the European Particle Physics Laboratory (CERN). ALICE is a data-intensive high-energy physics experiment at the boundary of nuclear and particle physics which, in this phase of operation, will take data though to the end of 2025. Working closely with UK collaborators the overall aim is to advance knowledge about the system created in the high-energy collisions at CERN's Large Hadron Collider and to advance the state-of the art in data science supporting the experimental programme. Objectives may include:

• Contributing to the data processing developments in the experiment
• Producing new scientific results for the experimental programme
• Developing new methods for data processing and analysis

Project description 

The ALICE experiment is collecting data of increased precision and reach, pursuing rare signals from the quark-gluon plasma. It has expanded its capability for collecting data and established a data processing pipeline that decides which data to keep, processes it in near real time and exports a condensed form for further reconstruction, These datasets are still of order 100 PB and are distributed over a worldwide computing grid for analysis by the user community. Further developments are still required and possible areas for this in the project include; the decision over which events to retain, known as triggering; the detection of anomalous detector conditions, affecting data taking; the efficient use of computing capacity by the users, through the development of new tools; the performance of algorithms for reconstruction and analysis, leading to final scientific results. Approaches to many of these developments are likely to involve machine learning or Al. At all stages collaboration with other members of the team or wider groups is essential.

The ideal candidate should have a good background in one of the areas of physics and computer science and a strong interest in the other, as well as the overall programme of research. Some previous programming experience is expected. A good undergraduate degree with research experience is required, preferably from a 4-year programme e.g. MPhys, MSci, MCompSci, or exceptionally from a BSc with a strong individual research component. Alternatively an MSc degree from a relevant area such as data science may demonstrate your aptitude for research.

Potential project impact 

The PhD studentship will contribute to the development of methods to increase the efficiency or precision of the experimental programme at ALICE. The sharing of methods and experience developed with industrial partners will be explored, with the potential to contribute to further REF impact case studies.

Principal accountabilities and responsibilities

The successful applicants are expected to:

• Apply their knowledge at the intersection of physics and data science and acquire other background knowledge as needed
• Implement their work in a variety of languages and platforms
• Contribute to high quality papers
• Communicate research results to a variety of audiences both specialised and more general
• Report progress in regular meetings with the supervisory team and members of the wider collaboration
• Be willing to undertake some international travel to CERN, located in the French-Swiss border area

To apply 

Please review our entry requirements before submitting your application and check out the 'Getting Started' section below.

Completed applications should be submitted via our online application system quoting funding reference: CoSE_PGRS_ALICEExpt_MAR23

Closing dates for applications: Monday 13th May at 5pm.*

*(Please note, we encourage applicants to apply as soon as possible as we reserve the right to close early, if a high volume of applications is received.)   

Interviews: Wednesday 29th May 2024 to Friday 7th June 2024. 

If you have not been invited for an interview by the interview date, please assume your application has been unsuccessful.  

For other enquiries which are subject-specific please contact:

Director of Studies (principal supervisor): Dr Lee Barnby (l.barnby@derby.ac.uk)

Supervisor (additional): Dr Mohsen Farid (m.farid@derby.ac.uk)

Find out more about our Data Science.

 Apply for this SE studentship post

Getting started

Before you begin your application, make sure you have:

Studentship funding reference code

This is provided on the individual studentship advert and must be specified in your application. 

Personal statement

A 500-word personal statement outlining your suitability for the studentship project. This is a mandatory requirement and you must upload it into your application. You should include your reasons for applying for the studentship, your experience in the field, how you feel you would benefit from studying and relevant information about your previous studies.

Your CV

A CV outlining your academic and professional experience.

Qualifications

Your qualification details including grades and dates taken. You will have the opportunity to upload scanned copies of your qualification certificates and transcripts in the application. If you have no formal qualifications, you can also state this in your application.

Passport/birth certificate

A scanned copy of your passport or full birth certificate. This will help us verify your application to study with us. International applicants can provide a copy of their passport only for visa assessment purposes, and their current visa if residing within the UK.

Academic references

Two signed academic references. This is optional at application stage but highly encouraged. If successful in your application, two academic references will be a mandatory requirement of admission. The references should be in written format, signed and dated from either a supervisor or tutor from your most recent studies.