Chemistry and AI Modeller

National Nuclear Labs · Risley, England

Chemistry and AI Modeller at National Nuclear Labs, based in Risley, England, paying £51,166 per annum. This is a permanent role.

Salary
£51,166 per annum
Location
Risley, England
Contract
Permanent
Posted
2 weeks ago
Closes
16 Aug 2026
Sector
Cleaner

About 83% above the going rate for cleaner

Reference 47ceb492b09c0fea21f72ae1fa5b9ad12ce7a2b1

About the role

Job Introduction

Job Description for Chemistry and AI Modeller:

This is where your skills play a critical role in keeping everyone safe. Working in Safety, Security & Safeguards gives you the chance to make your mark on some hugely interesting projects. UKNNL does work that nobody else in the sector is doing, and this means we need experts like you to make it possible, whilst keeping everyone safe. We’re committed to using nuclear science to benefit society for years to come. This means that you can build a long and successful career here whilst playing a meaningful role in delivering cleaner energy, reducing waste and keeping colleagues and the public out of harm’s way.

UKNNL has the purpose of “nuclear science to benefit society” which is supported by four focus areas: Clean Energy; Environmental Restoration; Health and Nuclear Medicine; Security and Safeguards. The Chemical Modelling team (CM) use computational modelling to address challenges within those focus areas, aligned to our purpose.

Within the focus area of Clean Energy, Environmental Restoration and Security and Non-proliferation we work across several areas including fuel performance for advanced nuclear reactors (advanced modular reactors) and other areas including heat applications from nuclear systems. Projects include work to develop flowsheets for synthesis of hydrogen utilising nuclear energy and projects understanding the behaviour of nuclear fuel under irradiation. Within the focus area of Environmental Restoration, we use process models to support the decommissioning of legacy nuclear facilities, for example by supporting plants and technologies that store radioactive waste, treat wastewater, and immobilise waste, thus minimising its environmental impact. We develop chemical models to underpin these flowsheets for chemical plants supporting the clean up and decommissioning of Sellafield site.

Our capability is based on our ability to model chemistry across different length and time-scales (multi-scale modelling). Core capabilities include Density Functional Theory, Molecular Dynamics Simulation, thermodynamic modelling (Calphad and aqueous methods for modelling solubility and speciation, such as those in PHREEQC) and rate theory modelling. Increasingly, AI is an important capability, and knowledge and practical experience of AI & Machine Learning is essential.

The chemical modelling team consists of a combination of scientists and engineers at PhD level. We are a small vibrant team, the majority of whom are early in their nuclear energy career. In joining our team, the successful candidate will have the opportunity to work on a wide range of industrially relevant problems.

For this vacancy we require a candidate with molecular dynamics expertise to take on several current and future projects in this area, however the role is adaptable, with further opportunities to develop new skills in support of UKNNL’s mission. Applications include nuclear fuel and structural materials modelling, waste modelling, physical property predictions. The candidate will have the opportunity to develop their own niche in this area and expand into supporting different areas of the business. Collaboration with research organisations on projects is increasingly important to UKNNL, and experience of developing and delivery of UKRI funded research projects is highly desirable.

Main Responsibilities for Chemistry and AI Modeller:

  • Identify opportunities working with commercial functions and customers and prepare scopes of work under direction of a technical lead.
  • Develop partnerships with academia and industry to develop opportunities for UKRI funding.
  • Develop expertise in their field supporting UKNNL in the delivery of its mission against focus areas including clean energy and environmental restoration.
  • Deliver work to customers against a pre-defined schedule, agreed budget and to a high level of technical quality.
  • Report progress to team and project managers, flagging up issues and opportunities that arise when delivering the work.
  • Develop and maintain models including bespoke coding in scientific programming languages as required.
  • Carry out computer simulations as part of research and development activities.
  • Report findings to customers via technical reports.
  • Present work to customers and other external stakeholders.

Essential Criteria for Chemistry and AI Modeller:

  • Hold a 1st degree in Chemistry or a closely related subject.
  • PhD in related discipline including modelling the chemistry of materials using atomic scale simulation.
  • Experience of machine learning and statistical methods.
  • Experience of writing technical reports and/ or journal publications as first author.
  • Ability to obtain BPSS level security clearance (this includes but is not limited to identity, employment and criminal record checks).

Desirable Criteria for Chemistry and AI Modeller:

  • Experience of molecular dynamics simulation and other classical methods for atomic scale simulation such as Grand-Canonical or kinetic Monte Carlo.
  • Programming/ development experience with a scientific programming language (Matlab, Python, R, Fortran etc).

Why join us?

UKNNL isn’t just a place where you can do career-defining work that makes a real-world impact. It’s also a place where you’ll feel appreciated and valued. We’re creating an inclusive workplace where everyone is free to be themselves and feel like they belong. We put your wellbeing first, we push you to reach your potential, and we do everything possible to help you feel safe, supported and inspired.

We also offer a range of employee benefits:

  • Sector leading Family-Focused Policies: celebrate life events, including enhanced maternity and paternity leave and a week off for your marriage.
  • UKNNL offers attractive pension plans. If you contribute 5%, UKNNL contributes 15%. Alternatively, if you choose not to contribute (0%), UKNNL will still contribute 10%.
  • Annual Leave: Benefit from 25.5 days of leave, plus 4 extra days to be taken during Christmas shutdown, plus Bank Holidays.
  • Reduced gym membership with discounts of up to 25% from 3,700 gym and leisure providers across the UK
  • Company Bonus: Be rewarded for your contributions.
  • Learning Opportunities: Enhance your skills through excellent development programmes.
  • Employee Assistance: Access support for personal and professional challenges.
  • Cycle to Work: Stay active and eco-friendly.
  • Life Assurance: Ensure peace of mind for you and your loved ones.
  • Enhanced Sick Pay Benefits: Receive support during illness or injury.
  • Access to ‘Mydiscounts’ which has a range of special offers and discounts from more than 200 suppliers, including medical insurance and dental insurance.
  • Health Care: Health savings plan which allows you to claim money back on visits to the dentist, optician and/or physiotherapist (limits apply).

About The Company

UKNNL is an incredible place to work. A place where people do things that have never been done before. A place where people push boundaries to further themselves, the business and society as a whole.

This is a place where personal and professional opportunities are limitless. If you want to change the world, if you want to tackle climate change, if you want to help advance medical science, if you want to help put things in space, if you want to answer the big questions, if you want to work with extraordinary materials, if you want to meet great people, learn new skills, challenge yourself, work flexibly, and build a long successful career w

Reference: 47ceb492b09c0fea21f72ae1fa5b9ad12ce7a2b1 · Posted 2 weeks ago · Closes 16 Aug 2026 · Listed via National Nuclear Labs

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