Postdoctoral Research Fellow

The University Hospital Carl Gustav Carus and the Faculty of Medicine together form University Medicine Dresden. It is committed to excellence in high-performance medicine, medical research and teaching as well as healthcare services for patients in the entire region. The position is available starting December 1, 2026, on a full-time or part-time basis for a fixed term of 24 months. Remuneration is based on the provisions of the Collective Agreement for the Public Service of the Federal States (TV-L); classification in pay group E13 is possible, subject to the fulfillment of personal requirements. The research group of Prof. Dr. Nikolaos Perakakis is seeking for a highly motivated and talented Postdoctoral Research Fellow (max. 6 years from the acquisition of the doctoral degree) to join our interdisciplinary team at the Technische Universität Dresden, focusing on the integration of multi-omics data to better understand, diagnose, and treat metabolic diseases (i.e. obesity, diabetes, metabolic-dysfunction associated steatotic liver diseases).

• Conduct multi-omics data integration and advanced statistical analyses in ongoing and newly initiated projects on metabolic diseases
• Develop and apply machine learning models for biomarker discovery, patient stratification, and prediction of disease trajectories
• Collaborate with clinicians, bioinformaticians, systems biologists, and experimental researchers in a highly interdisciplinary setting
• Publish high-impact scientific papers and present results at national and international conferences
• Contribute to the supervision of PhD students and junior researchers

• PhD in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, or a related field – (Doctoral degree should not have been acquired earlier than 2021)
• Proven experience in the analysis of multi-omics data (proteomics, metabolomics, and/or genomics, transcriptomics)
• Strong expertise in machine learning and advanced statistical modeling
• Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries
• Experience with clinical and/or biomedical data and/or epidemiologic studies is highly desirable
• Strong publication record in relevant fields
• Experience in the field of immunology and of FACS analysis is a plus
• Ability to work independently and in a collaborative, interdisciplinary environment
• Excellent written and spoken English communication skills