Research Associate computational metabolomics (m/f/d) (7/2026)

de.NBI; Halle (Saale); Vor Ort; EUR 45.000 - 60.000; Vollzeit

Benefits dieser Stelle

Modern Working Conditions

Career Development

Ideal Working Environment

Team Spirit and Leadership Culture

Work-Life Balance

Zusammenfassung

de.NBI is seeking a Research Associate in computational metabolomics located in Halle (Saale), Germany. In this role, you'll develop methods for characterizing metabolites and utilize statistical techniques to analyze metabolomics data. A university degree or Ph.D. in relevant fields is required, along with strong programming skills in R, Python, and Java.

Enjoy modern working conditions, career development opportunities, and a collaborative environment that emphasizes work-life balance with flexible models and 30 days of leave.

Qualifikationen

• Strong knowledge of algorithms, software engineering, and statistics.
• Experience with statistical languages R, Python, and Java.
• Knowledge in metabolomics or chemistry is an advantage.

Aufgaben

• Development of methods for the characterization and identification of metabolites.
• Adaptation and use of statistical methods to detect patterns in metabolomics data.
• Integration of data from multiple omics experiments.

Kenntnisse

Algorithms

Software engineering

Statistics

R

Python

Java

Metabolomics knowledge

Ausbildung

University degree (master/diploma) or Ph.D. in computer science, bioinformatics, or related field

Jobbeschreibung

Research Associate computational metabolomics (m/f/d) (7/2026)

Research topic: As a (bio-) informatician, you will join our research group Computational Plant Biochemistry, which focuses on computational metabolomics and develops methods for processing and interpreting mass spectrometry data in the context of plant biochemistry and biodiversity research.

Responsibilities

• Development of methods for the characterization and identification of metabolites
• Adaptation and use of statistical methods to detect patterns and relevant connections in metabolomics data
• Integration of data from multiple omics experiments

Your profile

• University degree (master or diploma) or a Ph.D. in computer science, bioinformatics, or a related field
• Strong knowledge of algorithms, software engineering, and statistics
• Experience with the statistical languages R, Python, and Java
• Knowledge in metabolomics or chemistry is an advantage

Benefits

• Modern Working Conditions: Comprehensive introduction to work techniques and a modern research environment with state‑of‑the‑art equipment and up‑to‑date software.
• Career Development: Targeted training opportunities and access to a specialized library with electronic resources and quiet workspaces.
• Ideal Working Environment: A varied and inspiring workplace in an international setting at a leading scientific and innovation hub.
• Team Spirit and Leadership Culture: An open culture that strengthens teamwork, enables career networking, and promotes your research skills.
• Work‑Life Balance: Flexible working models, remote work options, and 30 days of annual leave.

About us

The Leibniz Institute of Plant Biochemistry (IPB) is a non‑university research institution of the Leibniz Association on the Weinberg Campus of the Martin Luther University Halle‑Wittenberg. As a foundation under public law, the IPB is under direct supervision of the state of Saxony‑Anhalt. The IPB is an internationally recognised research institution and consists of four scientific departments, additional independent junior research groups, and the Department Administration & Infrastructure (about 200 employees, including about 40 PhD students). Research at the IPB aims to understand the biochemical basis of plant resilience and performance in challenging environments related to climate change. The IPB offers excellent research facilities and state‑of‑the‑art infrastructure to investigate the chemical diversity, biochemical interactions, and biological roles of small natural molecules in plants and fungi, with an emphasis on specialised metabolites, chemical mediators, and relevant molecular networks of functional gene and protein regulation (https://www.ipb-halle.de/en/).