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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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the DFG-funded research project ICEBAY, which focuses on Bayesian hierarchical modeling and probabilistic inference for temperature reconstruction by combining borehole thermometry and ice-core data. The
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4‑year PhD position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and
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models in more detail using a wide range of methodologies and tools (e.g. molecular cloning and genome editing, immunoblotting, flow cytometry, high-resolution imaging and proteomics/terminomics). With its
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hotspots, and they are exceptionally beautiful. We will use a combination of molecular tools, quantitative genetics, and population genetic modelling to study genetic diversity in DNA sequence and phenotype
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models in more detail using a wide range of methodologies and tools (e.g. molecular cloning and genome editing, immunoblotting, flow cytometry, high-resolution imaging and proteomics/terminomics). With its
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to protect MN axons against degeneration in ALS. To achieve this objective, our team uses induced pluripotent stem cell (iPSC)-derived MNs to investigate RNP granule dynamics in a physiological model. We
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available in the further tabs (e.g. “Application requirements”). Programme Description International students holding a Master’s degree in (molecular) biology, (bio-)chemistry, physics, mathematics
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the field of model-driven and data-driven computational science. Job description Are you interested in bridging the gap between mathematical sciences on the one side and natural sciences, engineering and
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in living adaptive networks Biophysics: High-resolution structural and mechanical studies of molecular motor proteins at the nanoscale Required Documents Required Documents CV Certificates Motivation