Computational Scientist

About us
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 leads the way in realizing fusion energy, partnering with industry and research organisations to achieve ground-breaking advancements. Our goal is to bring fusion electricity to the grid by developing the power stations of tomorrow and the skilled workforce to deliver them.
About the job
A substantial part of the role will focus on FreeGSNKE, UKAEA’s open-source tool for modelling tokamak plasma equilibria and evolution. You will help develop and maintain the code, improve its performance on modern computing systems, and apply it to research challenges including plasma scenario design for MAST Upgrade and STEP. You will also contribute to work connecting numerical simulation with reduced-order models, AI-assisted applications and the emerging capabilities of the SUNRISE supercomputer.
What You’ll Be Doing
Develop and maintain FreeGSNKE’s Python codebase, including new modelling capabilities and improvements to performance and scalability.
Contribute to JAX-based FreeGSNKE development, including GPU-enabled simulation workflows and their deployment on SUNRISE.
Apply FreeGSNKE to plasma scenario design, benchmarking and simulation-based studies for MAST Upgrade, STEP and other fusion programmes.
Apply and validate FreeGSNKE through comparison with experimental data, benchmarking and simulation-based studies, including plasma scenario design for MAST Upgrade and STEP.
Contribute to reduced-order modelling, surrogate development and AI-assisted applications using simulation outputs.
Support internal and external collaborators using FreeGSNKE and contribute to scientific publications and conference presentations.
What You’ll Bring
Experience working in a Unix or Linux environment.
Knowledge of tokamak plasma physics, equilibrium modelling or scenario design would be advantageous.
Experience with high-performance computing, GPUs, JAX, or statistical and machine-learning methods would be welcome.
UKAEA is an onsite organisation, and this role requires regular onsite presence (usually between 3-5 days in any given week) in line with business needs. We actively support flexible working arrangements where this is compatible with the role.
Benefits
We have a generous range of benefits (see the full list here) and highlights include:
A salary of £43,702 (inclusive of a £3,300 specialist allowance)
Up to 7% corporate performance bonus
Final salary defined benefits pension scheme with an equivalent of 21.5% employer pension contribution
25 days annual leave plus 2.5 'privilege' days; 8 Bank Holidays
Additional 3 days of site closure over Christmas break
Flexible working options plus family-friendly leave provisions
Our commitment to ED&I
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, inclusion and accessibility, and strive to ensure fair representation across our workforce.
Please email talent@ukaea.uk if you have any questions or require adjustments to help you participate fairly in our recruitment process, for example changes to the way we interview or share information. As a Disability Confident Employer, we are committed to providing an inclusive and accessible recruitment experience for all candidates.
We particularly encourage applications from groups currently underrepresented in STEM, including women and people from diverse ethnic backgrounds. All appointments are made on merit and further information can be found here.

Employment type
Full-time

Work arrangement
Hybrid