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Leibniz-Institute for New Materials

PhD Student Positions in Machine Learning for Data-Driven Materials Design INM – Leibniz Institute for New Materials in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

Employment according to the German public service salary scale. The post is a full-time PhD position within an interdisciplinary research group; no stipend amount is stated.

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Country

Germany

University

Leibniz-Institute for New Materials

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Keywords

Computer Science
Machine Learning
Chemistry
Materials Science
Biology
Mathematics
Computational Chemistry
Computational Science
Active Learning
Generative Modeling
Atomistic Simulation
Physics
Interatomic Potential

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About this position

The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is inviting applications for several PhD student positions in the Data-Driven Materials Design group led by Prof. Viktor Zaverkin.

This research environment is highly interdisciplinary and connects the INM with Saarland University and the German Research Center for Artificial Intelligence (DFKI). The group works on machine learning for molecules and materials, with topics including machine-learned interatomic potentials (including atomistic foundation models), active learning and data generation strategies, data-driven acceleration of atomistic simulations, direct prediction of molecular and materials properties, and generative models for molecular and materials design.

Applicants should hold a Master’s degree in computer science, applied mathematics, physics, chemistry, materials science, or a related field. A background in machine learning, computational chemistry or materials science, atomistic simulations, or scientific computing is expected, along with scientific programming skills such as Python or PyTorch. Excellent English and the ability to work independently and collaboratively are also required.

The position offers an international research environment, access to modern computational infrastructure, opportunities for publications and conference presentations, and employment according to the German public service salary scale. The exact research topic will be defined together with the successful candidate based on interests and expertise.

Applications are reviewed continuously until the positions are filled. To apply, submit a single PDF via the online portal containing a motivation letter, CV, relevant certificates, and the names of 1–2 references.

Funding details

Employment according to the German public service salary scale. The post is a full-time PhD position within an interdisciplinary research group; no stipend amount is stated.

What's required

Master’s degree in computer science, applied mathematics, physics, chemistry, materials science, or a related field. Applicants should have a background in at least one of machine learning, computational chemistry or materials science, atomistic simulations, or scientific computing, plus scientific programming experience (e.g. Python, PyTorch, or similar tools). Strong interest in developing machine learning methods for modeling molecules and materials, ability to work independently and collaboratively in an interdisciplinary environment, and excellent written and spoken English are required.

How to apply

Apply via the online application portal and upload a single PDF containing your motivation letter, CV, relevant certificates, and the names of 1–2 references. Applications are reviewed continuously until the positions are filled.

More information can be found here

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