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As part of the MALOQ project, you will train state-of-the-art ML models to learn atomic, electronic, and vibrational properties of large-scale atomic systems representing the building blocks
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phosphorus-driven eutrophication, with experience in soil monitoring and erosion processes. Skills in GIS, spatial analysis of large scale data, modelling, remote sensing, and programming (R or Python
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in interdisciplinary research at the interface of biology, computational tools, and X-ray methods Experience with experiments at large-scale user facilities (e.g., synchrotrons or neutron sources) and
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disciplines. Desirable Skills and Experience (any of these skills help your application, but are not essential) Research Data Management: Experience with large-scale data curation, FAIR data principles, and
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for reaction-diffusion systems Enhancing the biophysical capabilities of the C++ framework Applying the framework to morphogenetic questions using real imaging data Running large-scale simulations on ETH’s HPC
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development. The project is in close collaboration with a large enterprise and focusses on the development of high-performance materials and materials systems based on, among others, silica aerogel. Key
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postdoctoral researcher in Robot Learning who is interested in questions such as: How can we fuse representations of the world with modern learning-based methods to allow for larger scale / longer horizon? How
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therapeutic targets. These efforts produce large-scale, rich in vivo perturbation datasets. The computational challenges include building scalable and reproducible pipelines for guide demultiplexing and
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for the analysis and visualization of large-scale biological datasets, available to researchers at DBM and the Biozentrum. The position is initially limited to 3 years and it is available immediately or upon
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) and willingness to work with large datasets Good command of English (spoken and written); a basic understanding of German is an advantage, but not mandatory Ability to work independently as well as in a