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Field
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optimal performance The PhD student will be supervised by Ida-Maria Sintorn, Professor in digital image processing, and Jens Sjölund, Assistant Professor in AI at the Department of Information Technology
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the subcellular to the patient level. PhD projects range from the analysis of basic cellular processes to clinical translation, from the application of novel biological approaches to the development of new imaging
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scientists with a vivid interest in interdisciplinary projects to image cell dynamics from the subcellular to the patient level. PhD projects range from the analysis of basic cellular processes to clinical
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 3 days ago
Framework Programme? Other EU programme Reference Number DC12 Is the Job related to staff position within a Research Infrastructure? Yes Offer Description 15 PhD positions in imaging of Nuclear architecture
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of human cohorts” (65%, Proteomics Group) Ref. Number: 396_2026 PhD Position 3 “Image-based analysis of human cohorts” (65%, Lipidomics Group) Ref. Number: 397_2026 PhD Position 4 “Data Science” (100
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processing and image representation Demonstratable experience in python for data handling and algorithm development Desirable : Knowledge and experience with imaging systems (X-ray CT, MRI or similar
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collaboration with partners with modelling expertise. This PhD offers the opportunity to work at the interface of plant physiology, root biology, imaging and quantitative analysis. The student’s work will provide
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project alongside 14 other PhD. students, all pushing the boundaries of quantitative imaging in plants. The ideal candidate profile: Must-have: MSc or equivalent degree (preferably in Life Sciences) Strong
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areas: AI/ML, image processing, molecular modeling and docking Strong experience in Python and C++ programming (knowledge of Fortran is a plus) Strong interest in interdisciplinary research bridging
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areas: AI/ML, image processing, molecular modeling and docking ‒ Strong experience in Python and C++ programming (knowledge of Fortran is a plus) ‒ Strong interest in interdisciplinary research bridging