Job Description

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

The Data Solutions Unit within UKAEA’s Computing Division delivers innovative research, development, and specialist support across data engineering, artificial intelligence, machine learning, FAIR data architectures, high-performance computing, and advanced digital technologies. Working at the forefront of fusion research, the team develops secure, scalable data solutions that enable scientists and engineers to optimise their work, accelerate discovery, and support the development of future fusion technologies through collaboration with academia, industry, and partners across UKAEA.

This is an opportunity to shape the future application of artificial intelligence in fusion research, working at the intersection of AI, HPC, and scientific discovery. As part of the Artificial Intelligence and Machine Learning team, you will provide research expertise in the application of AI/ML to complex fusion challenges. You will contribute to research programmes as part of a team of UKAEA and international collaborators, to develop innovative solutions using advanced computing environments, including High-Performance Computing (HPC). With significant autonomy, you will influence research directions, develop new opportunities, publish impactful research, and represent UKAEA as a leading voice in AI-enabled fusion research.

What you’ll be Doing

We are recruiting for multiple roles across the AI areas outlined below. If you are interested in applying, please indicate your preferred area(s) of interest as part of your application:

Enterprise AI Specialist:

• Corporate AI solutions (MS-Copilot, Google Gemini Enterprise)

• Data privacy/protection rules and UK government regulations (Export Control, regional Cloud deployment, data sovereignty)

• Open-source LLM deployment (Ollama, vLLM, Open WebUI)

• Large LLM deployment on parallel GPU architectures

• Advanced LLM applications (AI-assisted coding, LLM integration in engineering products)

• Knowledge Graphs (Neo4j, GraphRAGs)

Advanced Control Specialist:

• AI control methods (Reinforcement Learning, supervised learning, preference optimization)

• Applied control systems (Robotics, experimental control systems)

• Portability of AI/ML models onto control hardware (real-time workflows, compiled models, FPGA porting)

AI and HPC Specialist:

• Optimisation of AI workflows on parallel GPU architectures

• Porting of AI workflows on specialised hardware (Nvidia GH200, AMD Mi300x, Google TPUs, AWS)

• Large-scale deployment on Cloud Compute architectures

AI for Engineering applications Specialist:

• Application of AI to Digital Engineering workflows.

• Open-source CAD software (FreeCAD, OpenSCAD, LibreCAD)

• Proprietary Engineering software (Ansys, CATIA, Simulia, Siemens-NX)

• CAD Meshing for simulations (Gmsh, CGAL, CUBIT, Ansys-PyPrimeMesh)

• Engineering data visualisation (Blender, Omniverse, USD, VTK)

• Systems Engineering (MBSE, Ansys-Twin-Builder, Dassault-3DX)

Foundation Models Specialist:

• Transformers architectures

• Vision Transformer models

• Fine-tuning and transfer learning

• Scientific Foundation Models

• Large-scale data engineering

What you’ll Bring

• A PhD degree in a computational, mathematical or physical science discipline, with Post-Doctoral and professional experience (or equivalent experience in either a commercial or research environment), relevant to the area of AI/ML for fusion science.

• Recognised internationally as an expert in the field of AI for fusion

• Track record of publishing research in the area of AI for fusion, or a similar area of research with transferable knowledge to fusion science.

• Demonstrable experience of at least one compiled programming language (e.g. C++, Fortran, C, Rust) or advanced scripting language (e.g. Python Julia, R)

• Good experience of the UNIX operating system, particularly the command line interface

• Ability to work within a diverse team, but willingness to take significant personal responsibility

• Excellent written and spoken English

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 £64,820 (inclusive of a £6,500 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, 2.5 privilege days and 8 Bank Holidays

• 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

Additional information

International travels for short periods of 3-5 days are typical of roles at this level, to nurture collaborations and attend key conferences and workshops in this area of research.