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Miguel Caro

2 months ago

Postdoctoral Researchers in AI-driven Atomistic Modeling and AI-Accelerated Cheminformatics Aalto University in Finland

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral researcher positions funded by Business Finland project "Materials AI for accelerated industrial R&D". Salary is approximately 4148–4305 €/month depending on previous research experience. Contract includes occupational health care benefits and access to world-class supercomputing facilities through CSC, including LUMI and upcoming LUMI-AI upgrades.

Deadline

Aug 9, 2026

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Country

Finland

University

Aalto University

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Keywords

Computer Science
Chemistry
Chemical Engineering
Materials Science
Computational Chemistry
Molecular Dynamics
Python Programming
Density Functional Theory
High Performance Computing
Chemoinformatics
Physics
Post Doc

About this position

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.

Funding details

Postdoctoral researcher positions funded by Business Finland project "Materials AI for accelerated industrial R&D". Salary is approximately 4148–4305 €/month depending on previous research experience. Contract includes occupational health care benefits and access to world-class supercomputing facilities through CSC, including LUMI and upcoming LUMI-AI upgrades.

What's required

Applicants should have a doctoral degree in computational chemistry, physics, materials science, or an engineering doctoral degree in these areas. Candidates with a doctoral degree in computational biology, applied mathematics, or applied computer science may also be considered if their work is relevant to the project. Strong publication record, prior experience with high-performance computing systems, ability to work programmatically with data and software (for example Python scripting), and strong written and spoken English are expected. Practical experience in one or more of machine-learning interatomic potentials, density functional theory, chemical reaction modeling, enhanced sampling, molecular dynamics, or ML-based cheminformatics is preferred. Skills in scripting, high-performance programming, and ML libraries are beneficial.

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