|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||4 years at the UKRI rate (currently £15,921 per annum for 22/23)|
|Placed On:||30th November 2021|
|Closes:||11th February 2022|
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.
How to apply:
To apply, and for further details please visit the CDT website http://cdt-aimlac.org/cdt-apply.html and follow the instructions to apply online. This includes an online application for this project at http://www.bris.ac.uk/pg-howtoapply. 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.
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).
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.
Dr Sudarshan Paramesvaran (email@example.com), Prof. Henning Flaecher (firstname.lastname@example.org)
Subject Areas: Map your PhD to a maximum of 10 subject areas:
Particle Physics, Physics, Machine Learning, Data Science
Type / Role: