Materials Science Jobs

• Cambridge
• Hybrid · 3 days in office
• Permanent

Owns scientific delivery of partner projects from scoping to results, acting as a key technical contact alongside programme managers. Applies simulation, machine learning, data-driven optimisation or experiments to design and steer discovery campaigns, and translates between experimental, computational and ML teams. Also builds cross-cutting capabilities such as validated workflows, harmonised data pipelines and agentic design campaigns.

Git

• London
• Hybrid · 3 days in office
• Permanent

Owns the design of scientific data representations, schemas and ingestion pipelines that turn heterogeneous external materials data into ML-ready assets. Works with AI researchers and materials scientists to harmonise experimental and computational data from partners, defining quality, validation, lineage and provenance frameworks.

Pydantic · JSON Schema · pymatgen +7

• London
• Hybrid
• Senior
• Permanent · Part time

Lead the computationally guided design of a lipid nanoparticle delivery platform, applying chemical and biophysical principles to optimise LNP composition and formulation. Use AI-enabled chemistry, cheminformatics, predictive models and molecular modelling to prioritise formulation components, working closely with the experimental team and founding team in a small start-up.

• Sheffield
• On-site
• Permanent

Supports the industrialisation, optimisation and continuous improvement of Catalyst Coated Membrane manufacturing processes, including equipment specification, supplier engagement, FAT/SAT and commissioning. Works with the Principal Engineer and production teams on yield, throughput and cost improvements using Lean, PFMEA and Kaizen methods, maintaining SOPs and process documentation.

FAT/SAT · SOPs · PEM Electrolysers +1

• Abingdon
• Hybrid · 3 days in office
• £48,290 pa
• Permanent

Develops advanced HPC models to predict deformation and irradiation effects in metallic and ceramic materials for future fusion energy systems. Applies density functional theory, atomistic force fields and finite element simulations on national and international supercomputers, working within the EPSRC/EUROfusion programme and collaborating internationally.

• Stockton-on-Tees
• On-site
• £34,500 – £46,500 pa
• Senior
• Permanent

Lead technical delivery of small to medium process chemistry projects, designing and scaling polymerisation reactions from lab to pilot scale. Act as a technical specialist in acrylic and vinyl monomer chemistry, running hazard reviews and process safety work while mentoring junior scientists in a collaborative R&D team.

• Lyngby, Denmark
• Senior
• Permanent

Lead an internationally recognised research programme in X-ray-based characterisation, physics-based modelling and structural performance prediction of fibre-reinforced composites for wind turbine blades. The role combines X-ray computed tomography, finite element modelling and multiscale digitalisation, alongside teaching and supervision at BEng through PhD level and attracting external research funding.

X-Ray Computed Tomography · Finite Element Modelling

• London
• £52,790 – £73,271 pa
• Senior
• Permanent

Deliver undergraduate materials and polymer science education for a joint UK-China engineering school, with a focus on curriculum development, novel pedagogies and inclusive teaching. The post is based in London but involves extensive travel to Xi'an, China for substantial periods, supporting transnational education programmes.

• Retford
• Hybrid
• Lead · manages people
• Permanent

Lead an integrated team of internal staff and external specialists as Technical Authority for the STEP tokamak's jointed REBCO high-temperature superconducting magnets, driving design convergence, remountable joints and technology demonstration. The role spans risk mitigation, cross-functional working with plasma, power and project teams, supply chain development and team growth as the programme moves toward construction.

REBCO

• London
• Hybrid
• Mid-level
• Permanent

Builds and operates the software layer connecting an AI materials-discovery platform to partner laboratories worldwide. Designs APIs and data models for lab-to-cloud exchange, integrates instruments, robotic platforms and LIMS/ELN systems, and hardens integrations with retries, queueing and monitoring. Works in a small multidisciplinary team of materials scientists, ML and software engineers.

FastAPI · Pydantic · LIMS +5

• Cambridge
• Hybrid · 3 days in office
• Permanent

Trains and evaluates multi-modal foundation models for a materials discovery platform, spanning crystal structures, properties, text and images. Owns a model end to end, from data curation and experiment design through large-scale distributed training to integration, working closely with chemists and materials scientists.

GPUs · SFT · RLHF +1

• London
• Hybrid
• Entry level
• Permanent

Develop fast, accurate machine learning force fields distilled into lightweight student potentials for high-throughput Monte Carlo simulation, then integrate them into the in-house kUPS framework. The role involves curating training datasets, running validation campaigns against classical force-field baselines, and profiling the MC inner loop for throughput. Embedded in the chemistry team, with a publication on MLFF-driven GCMC for MOF screening.

kUPS · MLFFs · Equivariant Models +2

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Designs and builds agentic frameworks that orchestrate closed-loop scientific workflows, connecting agents to ML models, simulation engines and databases. Applies Bayesian optimization and active learning for experimental design, and builds evaluations for agent planning and decision-making. Works closely with chemists and materials scientists on customer projects.

PyTorch · JAX · LLM

• London
• Hybrid
• Mid-level
• Permanent

Builds and maintains a cloud-native ML infrastructure platform on Kubernetes, owning CI/CD pipelines, model registries, experiment tracking and deployment automation. Scales distributed GPU training for JAX and PyTorch workloads, manages multi-environment configs with Kapitan and Terraform, and drives platform reliability and cloud cost optimisation for research teams.

Kubernetes · AWS · GCP +7