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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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rhabdomyosarcoma), fragmented data from multiple small series has hampered global elementary understanding of metastasis biology and - therefore – targeted therapy development. It remains unresolved – and is
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then pursue M.D. or Ph.D. programs around the country, or pursue biomedical startup or industry careers. Responsibilities Research 80% - Run multiple projects in parallel, in collaboration with PhD
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. And it also allows you to operate multiple silicon carbide quantum systems in parallel, for the first time. (c) The final step is to demonstrate on-chip entanglement among two colour centres based
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. or Ph.D. programs around the country, or pursue biomedical startup or industry careers. Responsibilities Research 80% - Run multiple projects in parallel, in collaboration with PhD students and postdocs
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combined with soil sensors systems and UAVs with multispectral cameras. Your tasks in detail: Development and application of high resolution time-lapse GPR and EMI imaging methods at multiple scales
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working with high performance computers (e.g., parallelizing and distributing code). Experience in distributed data management and workflow systems. Preferred Competencies Ability to work independently and
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timetable for the four-year project to be submitted to DAAD. Development of relevant analytical methods and setting up of required laboratory equipment will be conducted in parallel. Execution of the research
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arises from a single overarching protective mechanism or from multiple fibre-specific adaptations that collectively enhance resistance to neuromuscular pathologies. Our preliminary work using single