FindAPhD Weekly PhD Newsletter | JOIN NOW FindAPhD Weekly PhD Newsletter | JOIN NOW

Searching for New Physics with the CMS experiment at the LHC

   School of Physics

This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  Dr Sudarshan Paramesvaran, Prof Henning Flaecher  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

UKRI Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) CDT

The project:

The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) aims at forming the next generation of AI innovators across a broad range of STEMM disciplines. The CDT provides advanced multi-disciplinary training in an inclusive, caring and open environment that nurture each individual student to achieve their full potential. Applications are encouraged from candidates from a diverse background that can positively contribute to the future of our society.

The CMS experiment at the Large Hadron Collider has already made ground-breaking discoveries since it started operating in 2010. However in 2025 the long awaited Run 3 of the LHC begins, and is set to double the entire dataset currently collected by CMS. This will lead to an unprecedented amount of data which will need to be carefully scrutinised to make sure we leave no stone unturned in our search for new physics. In particular, the search for signatures which exhibit large amounts of missing transverse momentum - a characteristic of particles escaping undetected - are especially interesting as they cast a wide net for new physics, including dark matter candidates and more exotic models such as split-susy. In this project we will develop machine learning (ML) algorithms to significantly enhance the discovery prospects from our newly collected data; a variety of different ML techniques will be studied to sift through the hundreds of millions of collision events looking for signs of new physics. These algorithms can be applied at all stages of analysis from trigger and reconstruction to event selection and background estimation.

Candidate requirements: 

Candidates should have completed an undergraduate degree (minimum 2(i) honours or equivalent) in a relevant subject, such as physics and astronomy, computer science, or mathematics.

Candidates should be interested in AI and big data challenges, and in the data from large science facilities research theme. You should have an aptitude and ability in computational thinking and methods including the ability to write software (or willingness to learn it).

How to apply:

To apply, and for further details please visit the CDT website and follow the instructions to apply online. This includes an online application for this project at Please select Physics (PhD) on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. Please make sure you include “AIMLAC CDT”, the title of studentship and the contact supervisor in your Personal Statement.


Dr Sudarshan Paramesvaran ([Email Address Removed]), Prof. Henning Flaecher ([Email Address Removed])

Funding Notes

The UK Research and Innovation (UKRI) fully-funded scholarships cover the full cost of 4 years tuition fees, a UKRI standard stipend of currently £15,921 per annum and additional funding for training, research and conference expenses. The scholarships are open to UK and international candidates.
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.

PhD saved successfully
View saved PhDs