Max Planck Institute of Biochemistry
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Postdoctoral Research Fellow in Bioinformatics and Machine Learning Max Planck Institute of Biochemistry in Germany
Degree Level
Postdoc
Field of study
Computer Science
Funding
Paid postdoctoral appointment with salary according to qualifications and TVöD (German public service tariff scale). Initial appointment is for two years with the possibility of extension.
Deadline
Sep 30, 2026
Country
Germany
University
Max Planck Institute of Biochemistry

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About this position
Max Planck Institute of Biochemistry in Martinsried near Munich is advertising a Postdoctoral Research Fellow (m/f/d) in Bioinformatics within the Department of Machine Learning and Systems Biology headed by Prof. Dr. Karsten Borgwardt.
The project focuses on developing machine learning methods for large-scale biological data and connecting predictive modeling with mechanistic understanding. Research applications include genome regulation, spatial proteomics, mass spectrometry, and protein design, using unique datasets generated at the institute.
This is a strong fit for candidates with a Ph.D. in bioinformatics, computational biology, machine learning, computer science, or related fields, especially those with experience in bioinformatic preprocessing pipelines and life-science data analysis. Excellent English skills are required.
The position is a paid postdoctoral appointment with salary according to TVöD. The initial contract is for two years, with the possibility of extension.
Applications should include a one-page motivation/personal statement, CV, bibliography, and contact details for at least two references. Submit via the online application portal by 2026-09-30. Informal inquiries may be sent to [email protected].
Funding details
Paid postdoctoral appointment with salary according to qualifications and TVöD (German public service tariff scale). Initial appointment is for two years with the possibility of extension.
What's required
Applicants must hold a Ph.D. in bioinformatics, computational biology, machine learning, computer science, or a related field. Strong interest and prior experience in developing and applying machine learning methods to life science problems are required. Experience with bioinformatic preprocessing pipelines for large-scale biological data is an advantage. Excellent written and oral English is essential.
How to apply
Prepare a one-page letter with a personal statement, CV, bibliography, and contact information for at least two references. Submit the complete application electronically through the application portal. Informal inquiries can be sent by email.
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