Plasma Turbulence Modeller

  • Abingdon Rd, Culham, UK
  • Full-time
  • Department: Tokamak Science
  • Salary: £36,397 to £52,293 (inclusive of MPP) + excellent benefits including outstanding pension
  • Confirmed Grade: Level 4 / Level 5
  • Site Location: UKAEA Culham, Oxfordshire

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.

Who are we looking for?

We are seeking a self-driven researcher with a PhD level of knowledge of plasma transport, turbulence and gyrokinetics (GK) to help develop models of turbulence in high beta spherical tokamaks, and to exploit first-principles-based approaches to seek optimal routes towards a viable fusion reactor based on the spherical tokamak.

Joining at an exciting time for UKAEA, you must have a passion for developing high quality models of plasma turbulence for fusion and will have experience of making contributions to GK codes developing either new physics capabilities or optimising performance.


Job Description

What will you be responsible for?

Working in a collaborative team contributing to an ambitious endeavour, you will be responsible for: 

  • Exploiting advanced gyrokinetic codes that are capable of modelling turbulence in high beta burning Spherical Tokamak (ST) plasmas (leadership in higher level)
  • Validating models by comparing simulations with data from MAST-U and other experiment (leadership in higher level)
  • Exploiting codes to simulate turbulence, and use these simulations to:
    • predict turbulence and transport in conceptual high beta burning STs
    • predict performance and explore routes to optimise ST reactor designs
    • improve reduced transport models that can be used in predictive transport codes. 
  • Guiding work by less experienced researchers (in higher level role)
  • Reporting results regularly via reports, and presentations both internally and to collaborators.
  • Disseminating outputs at conferences and in journals where appropriate.
  • Collaborating with GK modellers and developers based at UKAEA and in external collaborating organisations and submit bids for HPC resource.


Essential skills, experience and competence required

  • PhD (or about to hold PhD) in relevant field.
  • Interest in model validation by testing models against experiment (previous experience required for the higher-level role)
  • Experience in programming and HPC.
  • Research experience in numerical modelling of plasma turbulence with GK code(s) (substantial experience at least at PDRA level required for the higher-level role)
  • PhD level of knowledge of plasma turbulence, transport, and gyrokinetics (expert knowledge required for the higher-level role)
  • Publications in the field (strong track record of high-quality publications required for the higher level role)
  • Track record of strong independent and self-driven research.
  • Good team player.
  • Excellent oral and written communication skills.

In addition to the above, for the higher-level role, you will also be required to have:

  • Substantial research experience in plasma turbulence (at least at PDRA level).
  • Enthusiasm for leading or taking substantial roles in collaborative projects.

Desirable skills, experience and competence

  • Experience of working with UKAEA’s national/international collaborators.
  • Enthusiasm for collaborative projects
  • Experience in programming languages such as F90, C++, Python, and HPC software (MPI, OpenMP)
  • Familiar with modern software development practices
  • Experience of developing reduced models
  • Experience in guiding less experienced staff and/or supervising PhDs, or an interest in or aptitude for developing leadership

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, particular 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 Partner, with the support of our Inclusion Ambassadors, is actively promoting and advancing diversity and inclusion in the organisation to help make our organisation an employer of choice. We are easily accessible by car and are a 10 minute walk from Culham Railway Station.  

Please be advised that this vacancy may close earlier than stated 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.

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