PostDoc-Computational Materials Science & Scientific Software Engineering

Work Your Magic with us! Start your next chapter and join EMD Electronics.

Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.

Everything we do in EMD Electronics is to help us deliver on our purpose of being the company behind the companies, advancing digital living. We are dedicated to being the trusted supplier of high-tech materials, services and specialty chemicals for the electronics, automotive and cosmetics industries. We foster a global collaborative organization made up of individuals who have the passion to win, obsess about the customer, are relentlessly curious and act with urgency. Together, we push the boundaries of science to make more possible for our customers.

Location: San Jose, California | Remote Flexibility Available

Your Role

You will join an MLIP-powered computational platform for semiconductor materials discovery, working at the intersection of computational chemistry, scientific software engineering, and modern AI. You will design and implement production-grade Python workflows that connect first-principles calculations with machine-learned interatomic potentials to accelerate materials screening and deepen process understanding. You will develop end-to-end simulation pipelines, including slab generation, adsorption energy screening, and molecular dynamics, ensuring code is modular, tested, and well-documented.

You will run and analyze DFT calculations with Quantum ESPRESSO and VASP via ASE, generating high-quality training data for MLIPs and validating results against experimental benchmarks. You will evaluate and deploy MLIP frameworks (such as MACE or UMA), building robust training pipelines, validation protocols, and model-selection workflows. You will implement cheminformatics steps for molecular input preparation, SMILES handling, 3D conformer generation, binding site identification, and NEB-based transition-state searches, linking gas-phase properties to surface workflows. You will operate on HPC infrastructure with SLURM, containerization, and workflow orchestration to ensure reproducibility and scalability.

You will translate domain expert requirements into maintainable, production-grade software and contribute to coding standards, reviews, and CI/CD practices. You will stay curious about AI tooling and be ready to integrate new approaches into scientific workflows. You will collaborate across disciplines, communicating clearly with experimentalists, data scientists, and external partners while delivering tangible software that ships.