Automating Scientific Discovery in Physics using Hybrid AI Models

Primary supervisor

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Other projects with the same supervisor

Funding

  • Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

The increasing mathematical intricacy in different subfields of Physics define new barriers the interpretation of more complex physical phenomena and for the creation of new models. In order to tackle this increasing complexity, Physicists will require the support of new tools and methods which can augment and support their analysis and modeling process, exploring other media, beyond the traditional "pen and paper".

Artificial Intelligence techniques emerges as a natural candidate to facilitate the modeling work of Physicist under an increasing complexity scale.

This project will explore the application of natural language processing, machine learning models and automated symbolic-deductive reasoning techniques to support the creation of an analytical modeling assistant for complex systems in Condensed Matter Physics.

As a PhD student you will work at the interface between AI and Physics, understanding and encoding the conceptual complexity involved in the process of developing new models in Condensed Matter Physics, using the extensive palette of tools available in the AI community.

The project will be done in close collaboration and co-supervision of Dr. Alessandro Principi from the School of Physics and Astronomy at the University of Manchester.

Applicants are expected to have:

* An excellent undergraduate degree in Computer Science or Mathematics (or related discipline), and preferably, a relevant M.Sc. degree.
* Confidence and independence in programming complex systems in Java or Python.
* Previous academic or industry experience in Natural Language Processing or Machine Learning (desired).
* Excellent report writing and presentation skills.

Please note that applicants must additionally satisfy the standard requirements for postgraduate studies at the University of Manchester, such as a first-class or high upper-second class (or an equivalent international qualification) and English language qualifications, as stated in the PGR guidelines.

Qualified applicants are strongly encouraged to informally contact Andre Freitas (andre.freitas@manchester.ac.uk) to discuss the application prior to applying.

Person specification

For information

Essential

Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.

Desirable

Applicants will be required to evidence the following skills and qualifications.

  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
  • You will have good time management.

General

Applicants will be required to address the following.

  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Why do you believe you are suitable for doing Postgraduate Research?
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