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individual with a MSc degree in computer science, mathematics, chemistry, computational biology or a related subject. The ideal candidate has familiarity with one or more of the following areas: algorithmics
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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and developmental biology, mechanobiology, stem cells and differentiation, network reconstruction and systems biology, proteomics, genomics, metabolomics, sequencing and algorithms, computational
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Media (EDM), the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms, Implementations (RTG π³), the UBRA AI Center for Health Care , and the ZeMKI
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Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or related discipline. * At least 1 year of experience in bioinformatics research. * Quantitative training with good understanding
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programme with a focus on data science and research in the structure of matter. The graduate school covers data challenges from application fields such as structural biology, particle physics, photon science
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, their achievements and productivity to the success of the whole institution. At the Cluster of Excellence „Physics of Life” (PoL), the Heisenberg Chair of Biological Algorithms (Prof. Dr. Benjamin Friedrich) offers a
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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Spintronics, Complex systems, Theoretical Mathematical Science, Big Data, Mechanobiology / Physical Biology, Bio-energy, Genetic to Physiology, Mental Health, High Performance Computation in Physics, Chemistry