Back to search results

PhD in Artificial Intelligence Approaches to Quantum Materials: Characterising Topological Order

University of Kent

Qualification Type: PhD
Location: Canterbury
Funding for: UK Students, EU Students
Funding amount: £14,777
Hours: Full Time
Placed On: 10th January 2019
Closes: 8th February 2019

Supervisors: Dr S J Gibson, Dr G Moller, Dr J Quintanilla

A PhD position is available in the field of Artificial Intelligence Approaches to Quantum Materials. This project is in competition with other projects offered by the School of Physical Sciences for one of a number of EPSRC Doctoral Training Partnership Studentships.

The aim of the project is to harness techniques from the field of Machine Learning to characterise topological order in advanced materials.

Over the last decade, Artificial Intelligence approaches such as Machine Learning have become prevalent in many areas including autonomous (self-driving) vehicles, recommender systems and healthcare. More recently the application of such approaches to the discovery and understanding of condensed matter systems, including advanced quantum materials, is emerging as a novel approach with the potential to revolutionise the field.

The present project leverages a unique blend of expertise within the University of Kent’s School of Physical Sciences (SPS), including a world-class research programme in Condensed Matter Theory and cutting-edge applications of AI. Examples of relevant SPS research include the discovery of novel superconducting states, new ways to characterise topological states of matter, and a facial identification method using brainwaves.

Topological order is a new paradigm for quantum materials and leads to many novel phenomena, including topologically-protected excitations that may form the building block of future quantum computers. The successful candidate will develop new machine-learning based strategies for characterising topological order in condensed-matter systems.

The successful candidate will be based at the University of Kent's main campus in Canterbury and will be a member of the Quantum Theory and Simulation Activity within the Functional Materials Group.

This PhD Studentship is due to start in September, 2019.

Entry requirements and funding: Applicants should have or expect to obtain a first or upper second class honours degree (or equivalent) in Physics, Mathematics, Computer Science, or a related subject. A strong theoretical or computational would be an advantage. This is in competition with other projects for an EPSRC-funded Scholarship, which will be offered at the standard UK Research Councils' rate (currently £14,777; to cover living costs) and will additionally cover tuition fees at the Home/EU rate (currently £4260 per annum). This scholarship (maintenance and fees) is available to UK nationals only, but EU nationals are eligible for a fees-only award.

Webpage(s):

Contact: For further information or informal enquiries, please contact Dr S J Gibson (s.j.gibson@kent.ac.uk), Dr G Möller (g.moller@kent.ac.uk), or Dr J Quintanilla (j.quintanilla@kent.ac.uk).

How to Apply: To apply please go to https://www.kent.ac.uk/courses/postgraduate/212/physics

You will need to apply through the online application form on the main University website. Please note that you will be expected to provide personal details, education and employment history and supporting documentation (Curriculum Vitae, transcript of results, two academic references).

Deadline Date for Applications: 8 February 2019

Interviews to be held between: 25 February – 8 March 2019

   
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
 
 
 
 
More PhDs from University of Kent

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