Back to search results

PhD Studentship: Searching for New Physics with the CMS Experiment at the LHC

University of Bristol - UKRI Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) CDT

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students, International Students
Funding amount: 4 years at the UKRI rate (currently £15,921 per annum for 22/23)
Hours: Full Time
Placed On: 30th November 2021
Closes: 11th February 2022

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.

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.

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).

Funding:

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.

Contacts:

Dr Sudarshan Paramesvaran (sudarshan.paramesvaran@bristol.ac.uk), Prof. Henning Flaecher (henning.flaecher@bristol.ac.uk)

Subject Areas: Map your PhD to a maximum of 10 subject areas:

Particle Physics, Physics, Machine Learning, Data Science

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):

Location(s):

PhD tools
 

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Ok Ok

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Manage your job alerts Manage your job alerts

Account Verification Missing

In order to create multiple job alerts, you must first verify your email address to complete your account creation

Request verification email Request verification email

jobs.ac.uk Account Required

In order to create multiple alerts, you must create a jobs.ac.uk jobseeker account

Create Account Create Account

Alert Creation Failed

Unfortunately, your account is currently blocked. Please login to unblock your account.

Email Address Blocked

We received a delivery failure message when attempting to send you an email and therefore your email address has been blocked. You will not receive job alerts until your email address is unblocked. To do so, please choose from one of the two options below.

Max Alerts Reached

A maximum of 5 Job Alerts can be created against your account. Please remove an existing alert in order to create this new Job Alert

Manage your job alerts Manage your job alerts

Creation Failed

Unfortunately, your alert was not created at this time. Please try again.

Ok Ok

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

 
 
 
More PhDs from University of Bristol

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended

jobs.ac.uk has been optimised for the latest browsers.

For the best user experience, we recommend viewing jobs.ac.uk on one of the following:

Google Chrome Firefox Microsoft Edge