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Scientist for Generative AI Applications

Join our team!

FAIRmat is seeking a scientist for generative AI applications (TV-L E-13). 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

Your job is to develop an AI-driven "Copilot" to analyze NOMAD data. This position involves the following:

  • Work at the intersection of natural language processing (NLP), machine learning, and data analysis to create an intelligent assistant capable of simplifying data interactions for users through chatbot interfaces and automated analysis tools;
  • Prompting and fine-tuning of large language models;
  • Development of retrieval-augmented generation systems;
  • Close interaction with domain experts (e.g., experimentalists) to get feedback on your tools and to optimize them for their needs.

Requirements

  • Academic degree at the Master’s level or higher in Computer Science, Data Science, Artificial Intelligence, or Data-driven methods in a scientific or engineering field or a related field;
  • Very good programming skills in Python;
  • Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or similar;
  • Experience in software development with Linux, Docker, and Git;
  • Experience with retrieving data from REST APIs and databases;
  • Preferably, experience with retrieval augmented generation techniques and LLM fine-tuning;
  • Ability to interact and communicate with experts from different scientific fields;
  • Excellent verbal and written communication skills in English. Proficiency in German is a plus. 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 data infrastructure for materials science research data, embracing data from materials synthesis, experimental characterization, computational materials science, 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? To apply, please submit a single PDF file containing your motivation letter, CV, certificates, and references by e-mail to Victoria Coors and Pepe Márquez (fairmat@physik.hu-berlin.de).

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