Data Expert for Classical Molecular Simulations

Join our team!

FAIRmat is seeking an expert for data from classical molecular simulations  (TV-L E13). Join the dynamic FAIRmat team at its headquarters at the Humboldt-Universität zu Berlin and work towards shaping the future of research data management and materials science! All genders are encouraged to apply.

Job Description

  • You will be responsible for expanding support for classical simulations (e.g. molecular dynamics, Monte Carlo, multiscale modeling) within the consortium FAIRmat.
  • You will work within FAIRmat’s computational development team to harmonize with descriptions of electronic structure calculations and excited states workflows.
  • You will build and maintain a network of stakeholders to identify interesting use-cases and facilitate the development of associated infrastructure for these applications  (depending on the applicant’s background, this task may be focused towards harmonizing the treatment of biophysical data from both classical simulations and experimental techniques).



  • Academic degree (master or similar) or Ph.D. in physics, computer science, biophysics, life sciences, materials science, or another relevant field.
  • Excellent programming skills in Python.
  • Expertise in classical molecular simulations (experience with biomolecular systems or knowledge of biophysical techniques is a plus).
  • Experience with data processing, using APIs, databases, and advanced image analysis is a plus.
  • Experience in developing ontologies is a plus.
  • Ability to interact and communicate with experts from different scientific fields.
  • Excellent verbal and written communication skills in English and possibly also in German.
  • Strong teamwork skills and enthusiasm for bringing together people with diverse backgrounds and interests.

What we offer

A stimulating, multidisciplinary working environment, a pay scale classification (TV-L), ample development opportunities, and flexible working hours. The majority of the FAIRmat team is based at the Humboldt-Universität zu Berlin. The project is funded until September 30, 2026 with prospect towards prolongation. 

Who we are

FAIRmat stands for FAIR Data Infrastructure for Condensed-Matter Physics and the Chemical Physics of Solids. FAIRmat is a consortium of the National Research Data Infrastructure NFDI. We are building a FAIR data infrastructure for materials science and related research areas. FAIRmat develops NOMAD, the largest database for computational materials science research data, worldwide. We are currently advancing our data infrastructure towards materials synthesis, experimental physics, theory, and data processing workflows. This new digital infrastructure, based on leading-edge IT technologies, supports Open Data and Open Science towards data-centric materials science.

... Interested in joining FAIRmat?

Excited by the prospect of joining us? Send us your application (single pdf containing your motivation letter, cv, certificates, and 3 references) by e-mail to Victoria Coors (