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).
Postdoctoral Research Fellow (m/f/d)
Multi-Omics Data Analysis & Machine Learning in Metabolic Diseases
Full-time in Dresden, minimum 2 years (TV-L renumeration) : starting November 1st, 2026 or at the earliest convenient timepoint.
Our group is part of a vibrant scientific community at the TU Dresden and works closely with national and international partners within initiatives such as the German Center for Diabetes Research (DZD) and the Trans Campus collaboration with King's College London. We analyze large clinical cohorts and experimental models to unravel disease mechanisms and identify novel biomarkers by integrating proteomics, metabolomics, and genomics / transcriptomics data with machine learning techniques.
Job Description
• 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.
Candidate Profile
• 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 (e.g., scikit-learn,
TensorFlow/PyTorch, Bioconductor).
• Experience with clinical and/or biomedical data is highly desirable.
• Experience in the field of immunology and of FACS analysis is a plus.
• Strong publication record in relevant fields.
• Ability to work independently and in a collaborative, interdisciplinary environment.
• Excellent written and spoken English communication skills
• A stimulating and collaborative research environment within the Technische Universität Dresden, the Paul Langerhans Institute of
Dresden (PLID) - part of the German Center for Diabetes Research (DZD) and the TransCampus initiative.
• Access to large, well-characterized clinical cohorts and experimental models.
• Opportunities to contribute to high-impact translational research with real-world relevance for metabolic disease patients.
• Opportunities for professional development, career mentoring, and networking.
• Full-time position funded for up to 3 years, salary according to TV-L, plus standard benefits.
Application
Please send your application as a single PDF including :
• Cover letter (max. 1 page).
• Curriculum vitae with list of publications
• Contact details of at least two referees to : Nikolaos.Perakakis@ukdd.de
Application deadline : Applications will be considered on a rolling basis until the position is filled. Preferable starting date is the 1st of November 2026, but later start might also be possible. The TU Dresden is committed to diversity and equal opportunities. We encourage applications from all qualified individuals, regardless of gender, nationality, ethnic or social origin, disability, age, or sexual orientation.
See All B.Pharm Alerts M.Pharm Alerts M.Sc Alerts Ph.D Alerts
See All Other Jobs in our Database
Subscribe to Pharmatutor Job Alerts by Email
