Materials Science Jobs

CuspAI · London

Owns the full lifecycle of data-rich tools, services and web applications, building scalable ingestion, processing and cleaning pipelines for structured and unstructured materials-science data. Develops Python APIs and UIs for querying, exporting and visualising data, with orchestration, governance and containerised deployment using Docker and Kubernetes.

CuspAI · London

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.

PhysicsX · New York, United States · US$200,000 – US$250,000 pa

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) 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 · New York, United States · US$120,000 – US$240,000 pa

Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation engineers and customers. Owns data pipelines and production-ready models, and travels to customer sites 3-4 weeks per quarter to co-develop solutions on-site.

Airbus · Bristol

Lead fatigue and damage tolerance analysis for outer wing structures, acting as approval signatory and progressing toward full structural authorisation. Define and validate certification methods against CS-25 standards, liaise with EASA and Chief Engineering, and drive digital sizing tools and weight-saving initiatives. Also mentors engineers in first-principles stress analysis within a multidisciplinary wing analysis team.

Airbus · Bristol

Lead static stress analysis for Outer Wing structures, acting as an approval signatory and defining certification methods to CS-25 standards. Serve as technical focal point to EASA and Chief Engineering while mentoring engineers and deploying automated sizing tools such as ISAMI, GISEH and Nastran/HyperWorks.

CuspAI · London

Early security hire building automated security pipelines and AI-specific guardrails to protect frontier models, training data and proprietary IP. The role spans securing the ML lifecycle against prompt injection and data poisoning, embedding DevSecOps checks into CI/CD, and hardening cloud and Kubernetes environments with least-privilege IAM.

CuspAI · London

Owns a set of partner labs and their integration onto an AI materials-discovery platform, translating experimental workflows, instruments and LIMS/ELN data into engineering requirements. Leads technical discovery and onboarding through to first closed-loop campaigns, and works with ML researchers on Bayesian optimisation campaigns that respect real lab constraints.

CuspAI · London

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.

PhysicsX · New York, United States · US$200,000 – US$300,000 pa

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.

PhysicsX · New York, United States · US$240,000 – US$300,000 pa

Leads regional deployment engineering for a physics AI platform, owning end-to-end delivery into customer-owned infrastructure and acting as primary technical contact for CIOs and CTOs. Combines executive engagement with hands-on work on Kubernetes, cloud and infrastructure-as-code deployments, while hiring and scaling the regional team. Requires navigating regulated, high-security and on-prem/HPC environments.

PhysicsX · New York, United States

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.

PhysicsX · Singapore

Develops high-fidelity multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches. Owns the full simulation pipeline from geometry clean-up and meshing through solver setup, HPC runs and experimental validation, while building parametric CAD and Python automation for design optimisation and AI surrogate workflows.

PhysicsX · New York, United States

Builds and runs high-fidelity CFD models from geometry clean-up and meshing through simulation and post-processing, using Star-CCM+, OpenFOAM or Fluent on cloud and HPC resources. Works with data scientists and ML engineers to generate simulation datasets for deep learning surrogates, supporting customer engagements with occasional international travel.

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics and simulation challenges into mathematical formulations. You will train deep learning and probabilistic models on large spatiotemporal, geometric and point-cloud datasets, run experiment pipelines, and publish and present results with customers and partners.