Research Fellow In Machine Learning For Materials Design

London, ENG, GB, United Kingdom

Job Description

Ref Number


B04-06401

Professional Expertise


Research and Research Support

Department


UCL BEAMS (B04)

Location


London

Working Pattern


Full time

Salary


43,374 51,860

Contract Type


Fixed-term

Working Type


Hybrid

Available for Secondment


No

Closing Date


12-Sep-2025

About us


------------


The Chemistry Department at University College London is the oldest in England, and today is one of the best in the UK, being ranked 3rd in the UK for its world-leading research in REF2021. We are located in Bloomsbury, at the heart of London, and offer an exciting and vibrant environment in which to study in one of the UK's top universities. The Department of Chemistry at UCL is committed to supporting excellence in both research and teaching. The department offers undergraduate BSc and MSci programmes in Chemistry and currently teaches ~750 undergraduates registered in Chemistry as well as students who select Chemistry on the Natural Sciences programme and first year Chemistry for life scientists.



The department also offers a number of Postgraduate Taught Masters courses with about 80 students per year and has an overall PGR student school of about 200 students. The Chemistry Department has over 60 members of academic staff carrying out world-leading research. We specialise in the areas of organic synthesis, chemical biology, computational chemistry, nanotechnology, inorganic and materials chemistry, physical chemistry and chemical physics. The department has an annual research income of around 15 million, derived from many sources including the Research Councils (EPSRC, BBSRC, MRC, and NERC), European Commission and a wide range of charities and industrial partners in the UK, Europe and the USA.



Details about our research can be found on the departmental website http://www.ucl.ac.uk/chemistry


About the role


------------------


This post is funded through the EPSRC grant: Barocalorics for green cooling: from understanding to design. We seek to bring together a team of experimental and computational scientists to use the latest advances in machine learning and advanced characterisation to understand and design new materials for more sustainable cooling systems.



The appointee will be working in the Materials Design and Informatics Group based in UCL Chemistry and will be responsible for developing new machine learning models to understand the structure, dynamic and phase changing behaviour of a range of solid-state cooling materials. You will be part of the team collecting and analysing neutron scattering data. You will develop workflows for fitting new forcefield models designed to reproduce results from high-level electronic structure theory and neutron experiments. You will also develop new methods, drawing on concepts from information theory, to help understand and ultimately design for entropy changes across phase boundaries.



The project is a collaboration with Dr. Anthony Phillips at Queen Mary University of London whose group will synthesise new barocaloric materials and Dr. Helen Walker at ISIS Neutron and Muon Source, who will lead advanced characterisation of these systems. If you are passionate about the using simulation to understand cutting edge experimental data and was to push this field forward through the latest machine learning techniques, then we hope that you will apply.


About you


-------------


The postholder will be expected to conduct research focused on developing workflows for fitting machine-learned potentials to multi-modal experimental and theoretical reference data. This will include performing atomistic simulations to support and complement experimental studies, as well as creating new approaches to better understand and design for entropy changes within these systems.




What we offer


-----------------


As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:


41 Days holiday (27 days annual leave 8 bank holiday and closure days)

Additional 5 days' annual leave purchase scheme defined benefit career average revalued earnings pension scheme (CARE)

Cycle to work scheme and season ticket loan

Immigration Loan Relocation scheme for certain posts

On-Site nursery

On-Site gym

Enhanced maternity, paternity and adoption pay

Employee assistance programme: Staff Support Service Discounted medical insurance


Visit UCL rewards and benefits to find out more.



Reward and Benefits | Work at UCL - UCL - University College London




Our commitment to Equality, Diversity and Inclusion


-------------------------------------------------------


As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.



The Department has been awarded a Silver Athena Swan Award and we support the Athena beliefs that:


The advancement of science, engineering and technology (SET) is fundamental to quality of life across the globe.

It is vitally important that women are adequately represented in what has traditionally been, and is still, a male-dominated area.

Science cannot reach its full potential unless it can benefit from the talents of the whole population, and until women and men can benefit equally from the opportunities it affords.


Further information on Athena Swan is at https://www.advance-he.ac.uk/equality-charters/athena-swan-charter

Beware of fraud agents! do not pay money to get a job

MNCJobs.co.uk will not be responsible for any payment made to a third-party. All Terms of Use are applicable.


Job Detail

  • Job Id
    JD3538674
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    London, ENG, GB, United Kingdom
  • Education
    Not mentioned