Machine Learning Jobs in York

CureAge Therapeutics · London

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.

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

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

Partners with engineering teams to embed security into CI/CD pipelines, lead threat modeling and secure design reviews for web apps, APIs and cloud services, and run the product vulnerability lifecycle. Also drives secure coding standards, delivers hands-on training, and engages with customers during security reviews.

PhysicsX · Singapore

Develops multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches, non-Newtonian rheology and coupled reactive physics. Owns meshing strategy, parametric CAD-coupled simulation pipelines, HPC-scale transient runs and surrogate/ML-CFD workflows, working directly with customers to scope and validate models against experimental data.

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 develop deep learning and probabilistic models for physical systems, run large-scale experiments, and own research workstreams while publishing and presenting to customers and the community.

PhysicsX · Singapore

Builds and delivers high-fidelity multi-physics CFD models, from geometry clean-up and meshing to simulation and post-processing, integrating experimental data for validation. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for machine learning surrogates. Works on-site with customers and mentors junior colleagues, with global travel up to 2-3 weeks per quarter.

PhysicsX · Singapore

Lead technical delivery of physics AI solutions, architecting deep learning models and optimisation methods to predict and control physical systems. Build scalable production data pipelines, mentor junior team members, and collaborate on-site with customers across multiple regions to embed AI models into engineering tools.

PhysicsX · Singapore

Lead the deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Own scoping, architecture and success metrics for data/ML systems, mentor engineers, and work on-site with customers across North America, Europe, Asia and Oceania for 3-4 weeks per quarter.