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decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
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candidates will be involved in materials crystallography research in collaboration with other members of the Iversen group. The candidates must have a PhD in chemistry, crystallography, physics, materials
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medicine. The lab invented the RNA origami method that allows rational design of RNA scaffolds and devices for expression in cells [1] and have recently developed RNA origami robots that can sense, compute
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power. The project is funded by an ERC Starting Grant, the flagship funding program of the European Union, which supports frontier, cutting-edge research. Read more about the project here in an interview
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advice, and education. We offer professional laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international
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to quickly and accurately identify their subtype. At present, patient subtypes are decided using only clinical observations, and the process is highly suboptimal. For example, the available subtypes are often
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physically and functionally coupled across domains of life. The project will involve working with syntrophic deep-sea consortia, performing strictly anoxic physiological experiments, and developing electrode
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will