19 beste Stellen als machine learning in hürth, nw – aktuell auf Personalsuche

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machine learning jobs near hürth, nw

Research Associate in Biomedical Data Science and Bioinformatics (Postdoc or PhD student)

Rheinische Friedrich-Wilhelms-Universität Bonn -
Bonn

Jetzt bewerben

Details zur Stelle

Teilzeit
vor 9 Tagen

Leistungen

Homeoffice-Möglichkeit
Flexible Arbeitszeiten

Qualifikationen

Bioinformatik
R
Datenanalyse
Forschungserfahrung
Master
Bachelor
Machine Learning
Python

Vollständige Stellenbeschreibung

Published on: 06.07.2026

The University of Bonn is an international research university with a wide education and research profile. With a 200-year history, approximately 31,500 students, more than 6,000 staff, and an excellent reputation at home and abroad, the University of Bonn is one of the most important universities in Germany and is recognized as a university of excellence.

The Chair of Computational Life Sciences of the Bonn Center for Mathmatical Life Sciences is looking to fill the following position as soon as possible, on a fixed-term contract according to § 2 (1) WissZeitVG until the end of the project December 31, 2029 (postdoc position) or for three years (PhD student position):

Research Associate in Biomedical Data Science and Bioinformatics (Postdoc or PhD student, full- or part-time)

Center for Mathematical Life Sciences, Chair of Computational Life Sciences

The Computational Life Sciences group develops and applies novel mathematical, statistical, and computational approaches as well as software tools for data analysis and modeling. Through our close connections to the Hausdorff Center for Mathematics and the Excellence Cluster ImmunoSensation³ at the University of Bonn, we foster interdisciplinary exchange and provide methodological support for cutting-edge biomedical research.

We have an open position – either for a postdoc or for a PhD student – within the DFG-funded Collaborative Research Center/Transregio 333 “Brown and Beige Fat – Organ Crosstalk, Signaling and Energetics (BATenergy)” (www.trr333.uni-bonn.de). The consortium investigates the biology of brown and beige adipose tissue and its role in systemic metabolism. By combining experimental and computational approaches, BATenergy aims to uncover novel mechanisms of metabolic regulation and identify potential therapeutic strategies for obesity and related metabolic disorders.

Deadline:

July 26, 2026

Reference number:

2026/317

Working time model:

full- or part- time

Starting date:

as soon as possible

Duration:

temporary

Pay grade:

TV-L EG 13

Applications to:

[email protected]

Job posting (pdf)

Your tasks:

Depending on the position level, the following tasks and responsibilities will be carried out either under the guidance of experienced researchers (PhD candidate) or independently (Postdoctoral Researcher):

Bioinformatic, statistical, and machine learning-based analyses of publicly available and newly generated data from a wide range of technologies, including in vitro metabolic phenotyping, proteomics, single-cell RNA sequencing and spatial transcriptomics
Development and implementation of computational methods, software tools, and reproducible analysis pipelines for these analyses, with a focus on usability
Computational support, consulting, and collaboration with experimental and clinical partners within interdisciplinary research projects
Publication and presentation of scientific results at international conferences and in peer-reviewed journals
Supervision and mentoring of Bachelor’s and Master’s students.

We offer

A varied and challenging job with one of the largest employers in the region
Participation in high-impact interdisciplinary research in an international, stimulating environment with access to state-of-the-art technologies, datasets, and computational resources
The opportunity to pursue scientific qualification, e.g., to complete a doctorate
Occupational pension (VBL)
Many options available for university sports
Excellent access by public transport thanks to Bonn’s central location as well as the opportunity to take advantage of low-cost parking
Flexible working hours and the ability to work from home
Remuneration according to TV-L pay grade 13 (100% for postdoc position, 75% for PhD student position)

Your profile

PhD (for postdoc position) or university degree (master’s degree or equivalent, for PhD student position) in (bio)informatics, computational biology, computer science, statistics, mathematics, or a related quantitative discipline; alternatively, a degree in life sciences combined with a strong track record in computational data analysis
Profound knowledge of statistics, bioinformatics, machine learning, and/or data science methods
Experience in the analysis of large-scale biological datasets
Programming skills in R or Python
Interest in life sciences research, particularly metabolism, adipose tissue biology, and systems-level approaches to understanding metabolic diseases
Ability to work independently as well as collaboratively in an interdisciplinary research environment
Proficiency in written and spoken English

Diversity and equal opportunity

The University of Bonn promotes an open, respectful, and non-discriminatory academic culture and is actively committed to equal opportunity and family friendliness. We aim to eliminate structural disadvantages and to strengthen diversity in research, teaching, and administration. Therefore, we welcome all applications, regardless of ethnic or social background, gender, sexual orientation, religion or belief, disability, or age.

Applications from women and people with a documented severe disability (or equivalent status) will be given preferential consideration in accordance with the State Equality Act (LGG) NRW and Social Code (SGB) IX.

Contact

Prof. Dr. Jan Hasenauer

phone: +49 228 73-69446

E-Mail: [email protected]

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Research Associate in Biomedical Data Science and Bioinformatics (Postdoc or PhD student)

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Center for Mathematical Life Sciences, Chair of Computational Life Sciences

Your tasks:

We offer

Your profile

Diversity and equal opportunity

Contact

Prof. Dr. Jan Hasenauer

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