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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with
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on this work by using molecular methods to unravel the forces that modulate mutagenesis across the genome of mutagen-exposed cancer cells. You’ll be introduced to advanced statistical and computational methods
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access to international research networks dedicated and structured supervision comprehensive training and mentoring program free use of public transportation in Hessen (“state ticket”) We actively support
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
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The position is funded for 3 years (65% TV-L E13), starting on January 1st, 2026, within the framework of the TTU HIV program of the German Center for Infection Research (DZIF). Project Description: Although
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, giving rise to complex lesions. GSI is working on the quantification of such complex lesions in particular in dependence on radiation type. Within this program, the GSI biophysics department offers a PhD
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computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and experience in the analysis of metagenomics and/or biological high-throughput
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. The research program may also involve a numerical simulation component. Your tasks #analyzing measurements of ocean turbulence using autonomous glider vehicles #use and develop machine learning methods
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets