Materials Science Jobs

Rolls Royce · Bristol

Analytical engineering role supporting the Defence business across product design, development and certification. Day-to-day work spans structural and stress analysis, whole engine modelling, rotordynamics and vibration analysis, critical parts lifing, and durability and fatigue assessment. Requires a security check clearance and UK national status.

Rolls Royce · Derby

Analytical engineering role supporting Defence aerospace programmes across design, development and certification. Work covers structural and stress analysis, whole engine modelling, rotordynamics, vibration, critical parts lifing, durability and fatigue assessment, ensuring components perform safely in demanding environments. Requires a mechanical or aerospace engineering background and experience in regulated engineering settings.

PhysicsX · London

Build the simulation side of Large Physics Models, generating training data across fidelity levels and developing solvers in differentiable or GPU-native frameworks like JAX or Warp. Work in a research team alongside ML researchers, using commercial and open-source CFD tools to produce reference data and shape data-generation strategy.

PhysicsX · San Francisco, United States · US$150,000 – US$190,000 pa

Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point-cloud and mesh data, cloud and HPC infrastructure, and translating R&D outputs into reusable libraries and products.

PhysicsX · London

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

PhysicsX · Singapore

Deliver high-fidelity multi-physics CFD simulations for industrial customers, from geometry clean-up and meshing to post-processing and validation against experimental data. Build parametric CAD models and automate simulation pipelines for design optimisation and DoE studies, generating datasets for machine learning surrogates. Work alongside data scientists and ML engineers, mentor junior colleagues, and travel globally up to 2-3 weeks per quarter to work on-site with customers.

PhysicsX · Singapore

Lead technical delivery of physics AI solutions, architecting deep learning models and optimisation methods to predict and control physical systems. Work closely with simulation engineers and customers, building scalable production data pipelines and mentoring junior team members. Requires frequent travel to customer sites across multiple regions.

PhysicsX · Singapore

Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimization—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.

PhysicsX · Singapore

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure. Spans the full stack across complex engineering domains.