Data Scientists

Data Scientists

Overview of Responsibilities 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.

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.

• 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)

• AI control methods (Reinforcement Learning, supervised learning, preference optimisation)
• Applied control systems (Robotics, experimental control systems)
• Portability of AI/ML models onto control hardware (real-time workflows, compiled models, FPGA porting)

• 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

• 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-Py Prime Mesh )
• Engineering data visualisation (Blender, Omniverse, USD, VTK)
• Systems Engineering (MBSE, Ansys-Twin-Builder, Dassault-3DX)

• Transformers architectures
• Vision Transformer models
• Fine-tuning and transfer learning
• Scientific Foundation Models
• Large-scale data engineering

• 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…