Data Steward for Small-Molecule Omics and Research Data Management(m/w/x)

Beschreibung

You will drive open science by building sustainable data infrastructures and managing complex omics datasets, ensuring research remains reproducible, FAIR-compliant, and cutting-edge.

Anforderungen

• •MSc data science, data steward, or related
• •Experience with research data management and FAIR
• •Skills in large-scale raw data handling
• •Experience with database structures and omics repositories
• •Strong Python skills and workflow automation familiarity
• •Knowledge of statistical concepts and quality control
• •Excellent communication, documentation, and visualization skills
• •Very good English skills (German advantageous)
• •Ability to work independently and collaboratively
• •Strong organizational and project management skills
• •Independent, structured, service-oriented, and team player
• •Experience in interdisciplinary teams and research
• •Experience with open science and reproducibility
• •Teaching or training experience in data management
• •Contributions to collaborative research projects
• •Experience with international data standards (desirable)
• •Knowledge of university facility structures (desirable)
• •Experience abroad and supervising students (desirable)

Aufgaben

• •Carry out all position-related tasks independently
• •Participate actively in research and data infrastructure development
• •Support teaching and manage software and hardware administration
• •Advance research in mass spectrometry-based small-molecule omics
• •Establish and maintain robust data management practices
• •Curate qualitative and quantitative databases
• •Ensure long-term preservation and accessibility of data
• •Enable reproducible and FAIR-compliant research workflows
• •Collaborate with analytical scientists, bioinformaticians, and IT services
• •Build sustainable data infrastructures for multi-omics research
• •Maintain and upgrade quantitative biomolecular databases and metadata
• •Implement data management plans and FAIR principles
• •Develop standardized structures for raw and processed data
• •Design project-specific Data Management Plans for funding requirements
• •Collect and standardize experimental metadata and protocols
• •Annotate, document, and version raw and processed datasets
• •Harmonize data workflows across diverse omics platforms
• •Contribute to grant proposals for data infrastructure
• •Prepare SOPs, guidelines, and training materials
• •Train researchers in FAIR principles and computational workflows
• •Supervise students and researchers on data-related topics
• •Participate in quality assurance and departmental administration
• •Submit repository-ready datasets to public or institutional archives
• •Coordinate data archiving, backups, and security with IT

Tools & Technologien

Benefits