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Field
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. The research group led by Martin Enge is specialized in methodology-driven analysis of patient data, especially in the field of single-cell multiomics. We are a multidisciplinary group with expertise in both dry
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, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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an opportunity to network and get feedback on their work. Student profile: Some experience in data analysis would be very helpful, as would a working familiarity with a programming language (e.g. Python, R
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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, and theoretical analysis using Leslie-Ericksen theory for liquid crystal flow as well as theory for viscoelasticity of polymeric liquids. Both in the practical and simulation/theory work you will be
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imaging. Strong analytical skills and experience with medical imaging technologies and data analysis. The ability to work collaboratively in multidisciplinary teams and communicate effectively across
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bottom-up approaches for investigating the mechanisms of chaperone-mediated protein folding. Your responsibilities will include: conducting independent experimental work and perform data analysis
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Status: Closed Applications open: 15/05/2025 Applications close: 31/05/2025 View printable version [.pdf] About this scholarship Description/Applicant information This scholarship is funded as part
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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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(BIGS Mathematics) Teaching language English Languages Courses are held in English only. The thesis can be written either in German or English. Full-time / part-time full-time Programme duration 6