Materials Science Jobs in London

• London
• £23,805 pa
• Entry level
• Contract

Builds physics-informed surrogate models and process simulations within a Bayesian-optimisation loop, jointly searching design and process parameters with active learning to minimise costly physical builds. Traces manufacturing process to defects to mechanical and electrochemical performance across hand lay-up, AFP and continuous-fibre 3D printing, starting on flat coupons before pushing into curved and cylindrical geometry.

AFP · 3D Printing

• 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.

• New York, United States
• Hybrid
• Lead

Lead the ML approach to manufacturing and MRO data, from modelling through deployment in customer production environments across cloud, on-prem and edge. Build production ML on sparse, drifting sensor and process data, set uncertainty quantification and validation standards, and mentor engineers while travelling to customer sites worldwide.

PyTorch · Pandas · FastAPI +2

• New York, United States
• Hybrid
• US$200,000 – US$300,000 pa
• Director · manages people

Owns chemistry capabilities end to end, setting technical direction and leading a team across capability-building and customer delivery. Couples atomistic and molecular insight into continuum and systems-scale models, spanning DFT, machine learning interatomic potentials, and multiscale simulation for industrial materials and process problems.

DFT

• London
• Director · manages people

Leads the global Procurement PMO and governance framework, driving a value creation programme across roughly £1.7bn of spend with over 60 initiative owners. Partners with the VP Group Procurement and executive stakeholders on strategy, transformation, risk, budget and executive reporting, including the five-year roadmap.

Excel · Power BI · Source-to-Pay +1

• Harlow
• On-site
• Senior

Lead technical workstreams in R&D, designing and interpreting experimental programmes to develop polymer products, formulations and applications. Oversee laboratory, pilot plant and manufacturing trials, supporting scale-up, technology transfer and new product launches while troubleshooting production runs alongside manufacturing, commercial and regulatory teams.

• Sheffield
• On-site
• Permanent

Working within the stack design and verification team, you will develop and execute verification and validation plans for full-scale PEM electrolyser stacks and clamping skid frame systems. The role covers mechanical, hydraulic and thermal test programmes, prototype assembly and commissioning, plus data analysis using MATLAB or Python and reporting to internal engineering teams.

MATLAB · Python · PLC +1

• Sheffield
• On-site
• Mid-level · manages people
• Permanent

Leads the Product Conformity team managing stack and product certifications, technical construction files and regulatory documentation for global markets. Coordinates internal and external testing, hosts certification bodies, and performs final inspection of electrolyser products before dispatch as the voice of the customer. Works cross-functionally with engineering, quality, procurement, HSE and manufacturing to embed compliance across the product lifecycle.

ERP · MRP · Microsoft Office +5

• London
• Hybrid · 3 days in office
• Mid-level
• Permanent

Bridges frontier AI models and high-performance computing infrastructure by profiling large-scale training runs to improve Model FLOP Utilization and remove bottlenecks. Builds observability dashboards, optimizes NVIDIA GPU kernels and NCCL communication, and applies quantization, pruning and distillation to cut inference latency. Works closely with AI researchers and the infrastructure team on future cluster design.

NVIDIA · NCCL · Triton +7

• 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