PhD student in Clinical Bioinformatics (100 %)
Publication date:
15 May 2025Workload:
100%Contract type:
Permanent position- Place of work:Muttenz
Job summary
Join our dynamic team as a PhD student in clinical bioinformatics! This is a unique opportunity to impact diagnostic practices.
Tasks
- Develop machine learning algorithms to predict drug responses.
- Analyze multi-OMICs data for cancer diagnostics and therapy.
- Collaborate with clinicians and researchers to support treatment decisions.
Skills
- MSc in Bioinformatics or related field; programming skills required.
- Solid knowledge of cancer biology and OMICs data analysis.
- Excellent communication skills and team-oriented mindset.
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PhD student in Clinical Bioinformatics (100 %)
School of Life Sciences FHNW, Institute for Chemistry and Bioanalytics
We are seeking a highly motivated PhD student in clinical bioinformatics eager to make a meaningful impact on daily diagnostic practices at leading university hospitals. The successful candidate will play a pivotal role in integrating multi-OMICs data to predict drug responses and support molecular tumor boards, directly influencing clinical decision-making and personalized cancer treatment. This interdisciplinary position offers a unique opportunity to collaborate closely with clinicians and biomedical researchers, and to develop and apply cutting-edge machine learning models that help prioritize cancer therapies. The project is funded by the SNSF (Swiss National Science Foundation) and will be carried out in collaboration with the University of Zurich and the University Hospital Zurich. The working place will be at the FHNW new Campus Muttenz, just outside Basel, Switzerland.
- develop robust machine learning algorithms to predict drug response for clinical use
- identify and interpret alternative splicing changes relevant to cancer diagnostics and therapy
- analyze integrative genomics, transcriptomics, proteomics, and epigenetic datasets
- MSc degree in Bioinformatics, Computational Biology, or a closely related field
- solid programming skills (e.g., in Python or R) and experience with machine learning frameworks
- familiarity with cancer biology and OMICs data analysis (e.g., WGS, RNA-seq, proteomics)
- a team-oriented mindset with excellent communication skills
- proficient in English (spoken and written); German is an asset
www.fhnw.ch/en/about-fhnw/schools/lifesciences
