Technische Universität Dresden
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Postdoc in Multi-Omics Data Analysis & Machine Learning in Metabolic Diseases at Dresden University of Technology Dresden University of Technology in Germany
Degree Level
Postdoc
Field of study
Computer Science
Funding
Postdoctoral position for a minimum of 2 years and up to 3 years. Funding details such as salary or stipend are not stated.
Country
Germany
University
Technische Universität Dresden

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About this position
Postdoctoral opening at Dresden University of Technology in the Perakakis Lab, affiliated with the Paul Langerhans Institute and the German Center for Diabetes Research.
The project is a Postdoc in Multi-Omics Data Analysis & Machine Learning in Metabolic Diseases, with a focus on integrating multi-omics data to better understand, diagnose, and treat obesity, diabetes, and steatotic liver diseases.
The role includes conducting multi-omics integration and statistical analyses, developing machine learning models for biomarker discovery and patient stratification, collaborating with clinicians and bioinformaticians, publishing research, and supervising PhD students.
Applicants should have a background in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, or a related area. Strong experience with multi-omics, machine learning, Python/R, scikit-learn, TensorFlow/PyTorch, and Bioconductor is highlighted.
The position is based in Dresden, Germany, lasts 2 to 3 years, and starts on November 1, 2026. The post is open until filled.
To apply, email [email protected].
Funding details
Postdoctoral position for a minimum of 2 years and up to 3 years. Funding details such as salary or stipend are not stated.
What's required
Background in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, or a related field. Expertise in multi-omics, machine learning, Python/R, scikit-learn, TensorFlow/PyTorch, and Bioconductor is required or strongly preferred.
How to apply
Apply by email to [email protected]. The position is open until filled.
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