Turbulence Modeller
Overview of Responsibilities
The salary for this role is £48,290 (inclusive of a Specialist Allowance) . Onsite working is expected for 3 days a week, however, we actively support requests for flexible working.
This role can be based at any of the following sites: Culham, Oxfordshire.
This role requires employees to complete an online Baseline Personnel Security Standard (BPSS), including The Disclosure & Barring Service (DBS) checks for criminal convictions and possibly a search of open source data.
The Role
Are you looking for an exciting opportunity to make a difference? Join our team and contribute to the future of fusion energy. As Turbulence Modeller, you will play a pivotal role in developing and applying advanced computational tools to model turbulence and transport in high beta burning plasmas. You will focus on creating and refining reduced (quasilinear) models to capture key physics of turbulent transport efficiently, providing essential insights for optimising next-generation fusion pilot plants (FPP).
This work is integral to UKAEA’s ambitious STEP programme to design a compact fusion reactor foreseen
to operate in a non-inductive high beta plasma regime. In addition, UKAEA operates MAST-U, which as
one of the world’s leading spherical tokamaks, is highly suitable for exploring the physics basis for STEP.
The plasma regimes envisaged for FPPs like STEP push beyond the range of validity of reduced models
of turbulent transport. These models therefore require further development. In this endeavour, UKAEA
has strong collaborations with UK universities as well as other international programmes in Europe and
worldwide.
Key Responsibilities:
- Exploit codes that include physics required to model turbulence in high beta burning plasmas, e.g. fast alpha fusion products, electromagnetic fluctuations, flows etc.
- Build/refine reduced models to describe the turbulent transport obtained from higher fidelity models.
- May propose and participate in relevant experiments on MAST-U or other devices.
- Exploit and/or develop advanced computational tools (e.g. flux-driven transport calculations using gyrokinetic simulations and/or reduced models), and use these simulations to: improve reduced transport models, predict turbulence and transport in conceptual high beta burning plasmas, predict performance and explore routes to optimise reactor designs.
- Report results regularly via reports, and presentations both internally and to collaborators.
- Disseminate outputs at conferences and in journals where appropriate.
- Collaborate with turbulence modellers, developers and experimentalists based at UKAEA and in external collaborating organisations.
Qualifications
Essential Requirements:
- PhD (or equivalent experience) in relevant field.
- Experience in numerical modelling and/or validation of plasma turbulence models.
- PhD level of knowledge of plasma turbulence transport.
- Interest in model validation by testing models against experiment.
- Experience in a high-level programming language e.g. Python, MATLAB .
- Self-driven researcher.
- Good team player.
- Excellent oral and written communication skills.
- Relevant publications.
Additional Information
A full list of our benefits can be found here https://careers.ukaea.uk/life-at-ukaea/employee-benefits/
UKAEA’s mission is clean energy for all, and we welcome talented people from all backgrounds to help us achieve this goal. We are committed to equality, diversity, and inclusion and strive to ensure fair representation across our workforce. We particularly encourage applications from groups currently underrepresented in STEM, including women and individuals from diverse ethnic backgrounds, while ensuring all appointments are made on merit.
UK Atomic Energy Authority is committed to being accessible. Please email [email protected] if you have any questions or require help or adjustments to compete on a fair basis, for example, changes to the way we interview or share information.
Please note that vacancies are generally advertised for 4 weeks but may close earlier if we receive a large number of applications.