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research strategy, including fundamental and applied approaches You will create, process, analyze, and interpret the research data, prepare reports, and scientific publications You will take part and present
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corresponding to the organisational units of the University Hospital, it is one of the largest medical training and research institutions in Baden-Württemberg. Research focus of the Division and Postdoc Position
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within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or a
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career scientist with PhD(or equivalent) in Plant Biology, Biochemistry, Molecular Biology, Analytical Chemistry, or related field interested in integrated plant metabolomics and proteomics. Hands
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, molecular biotechnology and computational sciences. The modern Campus harbors the buildings of the science faculties and institutes, in direct vicinity to the University Hospital Heidelberg, the Max Planck
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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: subsidized Germany job ticket Our Corporate Health Management Program offers a holistic approach to your well-being Develop your full potential: access to the DKFZ International Postdoc Program and DKFZ Career
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to publications, presentations, and open-source tools related to the project. Your Profile Required Qualifications PhD in Bioinformatics, Computational Biology, Computer Science, Physics, or a related field. Strong
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field Strong publication record and experience in basic science or translational research Background in molecular oncology, tumor biology, liver-focused or immune-focused research, or computational
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, Computational Biology, Applied Mathematics or related field Interest in interdisciplinary research Applied experience with machine/deep learning methods Ability to handle multiple projects in a dynamic