Expert in Materials Characterization Data

vor 1 Woche


Berlin Metropolitan Area, Deutschland FAIRmat Vollzeit 80.000 € - 120.000 € pro Jahr

FAIRmat is seeking an 
expert for materials characterization data
 (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.

Details

  • Position: Expert for Materials Characterization Data
  • Employment Type: Full-time
  • Salary: equivalent to TV-L E13
  • Location: On-site position at the Humboldt-Universität zu Berlin in Berlin-Adlershof

Job Description

As part of our team, you will:

  • Develop materials characterization specific aspects within the consortium FAIRmat, and interact with internal and external partners.
  • Contribute to the development of NOMAD, a web-based application for managing, visualizing, and sharing scientific data with a focus on data from experiments.
  • Build and establish software tools, data models, standards and ontologies for materials experiments and harmonize them with data from synthesis & theory.
  • Help users apply and establish these tools for their research data management.
  • Possibility of shorter and, if necessary, longer stays at partner institutes, and presentation of our project at conferences and workshops.
  • Dissemination of project results in international peer-reviewed journals.

Requirements

To thrive in this role, you should bring:

  • An academic degree at Master's level or higher in physics, chemistry, materials science, computer science, or another relevant field.
  • Excellent understanding of scientific and experimental workflows in materials characterization — from data collection, processing, to advanced analysis tools.
  • Very good programming skills in Python.
  • Experience in software development with Linux, Docker, and Git.
  • Experience with data analysis and visualization, using APIs, and databases.
  • Experience in developing ontologies is a plus.
  • Experience in machine learning for experimental data is a plus.
  • Ability to communicate and collaborate effectively with experts from diverse scientific backgrounds, fostering teamwork and shared goals.
  • Excellent verbal and written communication skills in English.
  • Proficiency in German is a plus.

What we offer

A stimulating, multidisciplinary working environment, a pay scale classification (TV-L) and ample development opportunities. 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.

About FAIRmat

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.

Application

Excited by the prospect of joining us? Please submit your application as a single PDF file, which should include your 
motivation letter

CV

certificates
, and 
references
.

Send us your application by e-mail to Victoria Coors and Pepe Márquez ).


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