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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.

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Country

Germany

University

Technische Universität Dresden

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Keywords

Computer Science
Biomarker Research
Biostatistics
Biology
Computational Biology
Obesity
Systems Biology
Python Programming
Medical Science
Statistics
Insulin
Bioinformatic
ML

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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.

More information can be found here

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