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Head of LIBRTI Digital Science

Job in Abingdon, Oxfordshire, OX14, England, UK
Listing for: UK Atomic Energy Authority
Full Time position Listed on 2026-11-12
Job specializations:
Salary/Wage Range or Industry Benchmark: 95000 - 120000 GBP Yearly GBP 95000.00 120000.00 YEAR

Job Description & How to Apply Below

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 gridby developing the power stations of tomorrow and the skilled workforce to deliver them.

About

the job

Lead the digital science strategy for LIBRTI, a £220 million UKAEA flagship programme developing a world-first facility to demonstrate the feasibility of breeding tritium for fusion power. You'll bring together physics, materials science, computing and advanced modelling to develop the digital capabilities needed to design, validate and commercialise future fusion technologies. This is an opportunity to shape a pioneering area of applied science, lead a high-impact research team and help establish the UK's position at the forefront of fusion innovation.

What

You’ll Be Doing
  • Build relationships with incumbent and emerging digital specialists (from corporates such as GTD, Siemens, McLaren to SMEs such as Digi Lab) as well as UK Centres of Excellence (Turing, Hartree etc) to understand the art of the possible in full data integration strategies for £100M+ programmes in science and engineering.
  • Design, deliver and communicate, LIBRTI’s Digital Strategy, harnessing inputs from the Computing Division, Innovation Team and Commercial-Legal Team. This strategy must ensure FAIR (Findability, Accessibility, Interoperability, Reusability) compliance for a platform that must face the LIBRTI Facility’s future users, suppliers and operators.
  • Design the data capture and management system to integrate with the Facility control and instrumentation hardware/software such that LIBRTI is positioned on a technical trajectory towards a digital twin, ensuring that LIBRTI remains cutting edge in the longer term.
  • Design and deliver an R&D programme (~£2M/year through the Programme lifetime) via internal projects, PhD’s and contracted collaborations, to provide the code, code integration, uncertainty quantification required to support the Multiphysics (Digital Physics) platform for LIBRTI. The Multiphysics platform will integrate materials, engineering and nuclear data, with customer breeder blanket designs, to predict and then validate, tritium breeding at powerplant-relevant scales.

    This data output is ultimately, the commercial IP from LIBRTI which justifies this £200M+ taxpayer investment. This is a world-first area of scientific impact and requires moving in sync with USA national laboratories such as INL to ensure UK maintains first mover advantage overall.
  • Align LIBRTI digital platform and digital science strategy and tools with wider UKAEA intentions around the £100M+ STRIDE Programme and the UK Government’s AI aspirations within the Industrial Strategy.
  • Engage with senior stakeholders (UKAEA ExCo) to ensure LIBRTI digital strategy takes account of the broader organisation’s philosophies and aspirations around research data management and commercialisation.
  • Maintain a state-of-the-art knowledge in High-Performance Computing, Machine Learning, Large Language Models (LLM ~ AI) and a watching brief on Quantum Computing such that LIBRTI plans leverage what is feasible in the coming decade. This is a complex task in a rapidly and radically changing environment, where trade-offs must consider moving too slowly vs adopting before full risks are understood.
  • Act as senior line manager and technical manager, coaching and coordinating a team of LIBRTI scientists to support the derisking, design, delivery and dissemination of LIBRTI digital outputs (ranging from new…
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