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: algorithmics, graph transformation and algorithm engineering. Exposure to systems chemistry or systems biology is an asset but not a must. Proven competences in programming and ease with formal thinking are a
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). Maintenance of transgenic mouse colony and embryonic fetal analysis 3). Train students and post-docs in hematopoietic research techniques 4). Prepare figures. Make charts, tables, and graphs from numeric and
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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demonstrated experimental realizations and proven theoretical advantages. The project may involve several aspects, including mathematical theory, algorithm development, error correction, adaptation of GBS-based
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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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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sites. We will subsequently use information theory and (or) wavelet analysis to link this data with environmental variables and identify their principal drivers. Functional forms of LUE-WUE and gc will be
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large-scale MD simulations, ideally with LAMMPS, demonstrated via corresponding roles in publications Experience with density functional theory (DFT) calculations, ideally with VASP, demonstrated via
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computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably