Antti Karttunen

Aalto University is advertising several postdoctoral researcher positions in AI-driven atomistic modeling and AI-accelerated cheminformatics within the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), hosted by the Department of Chemistry and Materials Science in the School of Chemical Engineering. The project, Materials AI for accelerated industrial R&D , is funded by Business Finland and carried out with industry partners, the Finnish national supercomputing center CSC, and experimental collaborators. The research environment is strongly computational and interdisciplinary, combining computational chemistry , materials science , physics , computer science , and chemical engineering . Research topics include machine-learning interatomic potentials, high-throughput atomistic workflows, atomistic modeling of materials structure, molecular diffusion and surface interactions, reactions and thin-film growth, data-driven cheminformatics for molecular modeling/design, and molecular dynamics simulations. Useful experience includes Python or other scripting, HPC, Fortran/C/C++/CUDA, and ML libraries such as sklearn or PyTorch. Eligibility is aimed at candidates with a doctoral degree in computational chemistry, physics, materials science, or related engineering fields; applicants from computational biology, applied mathematics, or applied computer science may also be considered if their background fits the project. A strong publication record, HPC experience, and strong English communication skills are expected. The positions are postdoctoral roles, not PhD or MSc openings. The expected salary is approximately 4148–4305 €/month , depending on experience, and the contract includes occupational health care benefits. Researchers will also have access to CSC supercomputing resources, including LUMI and future LUMI-AI upgrades. Deadline: 9 August 2026. Applications are reviewed as they arrive, so early submission is encouraged. How to apply: Submit the application through Aalto University’s online recruitment system via the Apply now link. Prepare a one-page motivation letter, full CV, publication list, and contact details for at least two referees, all in English and as PDF files.