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addition to topological protection of electronic charge transport, such protection of propagating fluctuations of the magnetization – dubbed spin waves or magnons – has recently been gaining attention. This PhD project
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of their PhD. With the aim of better aligning the Award with the needs in the field and current developments in the academic landscape, the Academy encourages the nomination of researchers for their contribution
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in motor control by computational modelling and non-invasive brain stimulation. The focus of this project will be on advanced versions of transcranial alternating current stimulation (tACS), targeting
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related discipline. A solid background in de novo protein design, protein structure prediction (Rosetta, AlphaFold, …), protein expression, structure elucidation, machine learning, C/C++ and/or Python with
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modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning). Experience in annotation software such as ELAN and PRAAT. Existing peer-reviewed journal publications and conference
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on how to apply novel methodology. Deepen subject-matter knowledge through literature review and active engagement with current research developments. Work closely with academic advisors and collaborators
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 2 months ago
computer models as well as being in the lab. You have affinity with analytical determination of pharmaceuticals in difficult matrices. You are able to dive into topics outside your current knowledge base
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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and current quantum technologies, motivating the need for a powerful and practical alternative. In 2020 we introduced the concept of reconfigurable nonlinear processing units: RNPUs, Nature 577, 341-345
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong