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Computational Scientist: Image Analysis of Materials

Computational Scientist: Image Analysis of Materials

Company Description

By 2050, the planet could be using twice as much electricity compared to today. Are you interested in contributing and helping to shape the future of the world’s energy? If so, read on.

Fusion, the process that powers the Sun and Stars, is one of the most promising options for generating the cleaner, carbon-free energy that our world badly needs. UKAEA are at the forefront of realising energy from fusion, working with industry and research partners to deliver the ground-breaking developments that will underpin tomorrow's fusion power stations with the aim of bringing fusion electricity to the grid.

Job Description

Who are we looking for?

If you are familiar with methods and concepts used in computer vision and have experience in developing computer codes or numerical methods – with the ability to prepare research papers, this role could be a great fit for you.

UKAEA have an excellent opportunity for a Computational Scientist to apply methods of the rapidly developing field of computer vision, to the cutting edge of materials science, with an aim to help uncover the links between direct observations and the structure and properties of novel materials. 

This role is a part of a large collaborative European project, involving the UK, and will complement the extensive existing skills in experimental image acquisition and characterisation of a broad range of materials. The objective of the work is to develop ways of extracting information about the microscopic structure of materials, and how the observable properties of materials change over their lifetime. The data acquired from the images are expected to be used in compliance with the FAIR principles: Findable, Accessible, Interoperable and Reusable.

The appointee is going to join a successful team developing multi-scale models for simulating complex materials, with strong links with universities and research laboratories around the world.  

Responsibilities will include

  • Development of mathematical concepts and algorithms required for identifying and characterizing defect and dislocation microstructures observed experimentally
  • Production of an open-source code capable of automating microstructural characterization, together with associated unit tests and user documentation.
  • Carrying out analyses of micrographs provided by experimental groups at the Materials Research Facility (MRF) at UKAEA and further afield.
  • Interacting and collaborating with scientists involved in experimental materials science research at Materials Research Facility (MRF) at UKAEA 
  • Presenting results at scientific conferences and submission of publications to scientific journals (lead author on typically one journal publication per year, and co-author on others)

Essential skills, experience and competence required

  • PhD-level or equivalent experience in computer science, mathematics, physics, or computational materials science, with a publication track record, preferably using statistical or machine-learning based data analysis techniques.
  • Capable of working both alone and in a team.
  • The ability to quickly learn and implement new simulation algorithms having no prior experience.
  • The ability to quickly understand and appreciate how irradiation damage appears in experimental micrographs having no prior experience

The post-holder will have one or more of the following desirable attributes:

  • Experience in the development of computer codes and algorithms using one or several computer languages
  • Experience of preparing research proposals
  • Research experience in nuclear materials science, particularly in radiation damage mechanisms and effects on material properties
  • Experience of supervising, mentoring or training students
Additional Information

What we offer

  • A competitive salary  
  • A culture committed to being fully inclusive, supported by a Being Inclusive Strategy and Inclusion Ambassadors 
  • An Employee Assistance Programme and trained Mental Health First Aiders, with a full calendar of health and wellbeing initiatives 
  • Flexible working options including family friendly policies  
  • Emergency leave (paid) 
  • 30.5 days annual leave (including privilege days and 3 days between Christmas and New Year) increased with length of service 
  • Wide range of career development opportunities (e.g professional registration, internal promotions, coaching and mentoring programme)  
  • Outstanding defined benefit pension scheme  
  • Annual corporate bonus scheme  
  • Relocation allowance (if eligible) 

We welcome applications from under-represented groups, particularly from individuals from black and other ethnic minority backgrounds, including nationality and citizenship, people with disabilities, (visible and hidden) and women. Our dedicated ‘Equality, Diversity and Inclusion’ (EDI) partner, with the support from our Inclusion Ambassadors, is actively promoting EDI and taking steps to increase the diversity of our people through reinforcing best practice in recruitment and selection, and revaluating approaches where it is clear we can remove barriers to success. We are easily accessible by car and are a 10-minute walk from Culham Railway Station in Oxfordshire.

Please be advised that this vacancy is due to close on 07/05/21 . We may close earlier than this date if large or sufficient numbers of applications are received.

Please note all employees working at the UK Atomic Energy Authority will be required to complete an online Disclosure Certificate application as part of their clearance – The Disclosure & Barring Service (DBS) checks will show the details of all current criminal convictions (convictions considered unspent under the Rehabilitation of Offenders Act 1974) or will confirm that there are no such convictions.

Materials (MRF)
Type of Employment
£33,297 to £35,520 + excellent benefits including outstanding pension
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