The German Diabetes Center (DDZ), Leibniz Institute for Diabetes Research at the Heinrich Heine University (HHU) Düsseldorf, is an interdisciplinary research institute that integrates basic and clinical sciences to improve prevention, diagnosis and therapy of diabetes mellitus and its complications. The Institute for Clinical Biochemistry and Pathobiochemistry (Director: Prof. Dr. Hadi Al-Hasani) investigates the molecular mechanisms underlying the onset and progression of insulin resistance and type 2 diabetes. In a novel precision medicine approach, skeletal muscle samples from deep-phenotyped donors are analyzed using mass spectrometry based (phospho-)proteomics to investigate individual variations in insulin signaling across different diabetes subtypes (Turewicz et al. Nat. Commun. 2025, 16:1570). We are looking for a highly motivated and talented researcher in the life sciences who is interested in developing into computational biology as a
PhD Student in Computational Biology (m/w/d)
to join our international and collaborative team in an outstanding and competitive scientific environment.
Your Tasks
- Perform analyses of (phospho-)proteomics and associated clinical datasets, including statistical analysis and visualization of results.
- Use and further develop our existing data analysis pipeline for (phospho-)proteomics, donor profiling, pathway mapping and data visualization in the context of diabetes and precision medicine.
- Identify regulatory nodes and phosphorylation patterns associated with insulin resistance within insulin-signaling networks across different diabetes subtypes.
Your Profile
- Completed degree in biology, biochemistry, medicine, bioinformatics, data science or a related field.
- Background in life sciences, cell biology and protein biochemistry.
- Computational skills, including basic proficiency in programming (e.g., R, Python) and data analysis.
- Independent, creative thinker with a proactive mindset.
- High motivation to learn new skills in proteomics data analysis.
- Excellent communication skills in English.
Desirable Skills and Experience
- Experience in analyzing large-scale omics datasets and/or clinical data.
- Knowledge of statistics and/or data analysis using machine learning or AI methods.
- Skills in data visualization, data cleaning, and data preprocessing.
- Additional programming experience (e.g., C++, SQL, web development, workflow systems).
- Knowledge of HPLC, mass spectrometry and proteomics.
Our Offer
- Affiliation with the German Center for Diabetes Research (DZD) and the Leibniz Society, providing access to exceptional scientific resources, networks, and opportunities for career development, training, and mentoring.
- Support for independent, responsible, and flexible working practices.
- An initial contract of 2 years, with an extension envisaged.
- Family-friendly working conditions and a strong commitment to equal opportunities. Since May 2011, the DDZ has been certified by the "career and family audit". The provision of §7 (1) of the Part-Time and Fixed-Term Act is taken into account.
- Salary according to the collective agreement for the public service of the federal states (TV-L, 65%) in the version applicable in North Rhine-Westphalia.
- Preference given to applicants with severe disabilities in cases of equal qualification.
- Preference given to women in cases of equal qualification.
The institute participates in the Multi-Omics Data Science network (MODS; https://www.mods.hhu.de/en). For further information on the project, please contact Dr. Michael Turewicz (email). Please submit your complete application (motivation letter, CV, certificates/records) until 2026-04-16 with the reference code IKB-PDCD-26-1 via email. The registration and further processing of your application is carried out in the DDZ primarily by electronic data processing. The data protection regulations apply. By applying, the candidate agrees to this procedure.
Deutsche Diabetes-Forschungsgesellschaft e.V.
- Personalwirtschaft - Auf’m Hennekamp 65, 40225 Düsseldorf
www.ddz.de
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und verwende die folgende Referenznummer:
IKB-PDCD-26-1
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