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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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and computational modeling to understand complex biological processes. Experience in statistical modeling, machine learning, or analysis of spatial or high-dimensional biological data is considered
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and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
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The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
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nomination Continue nomination The selection procedure Icon Applicants Applicants Icon Foundation Foundation Icon Notification Notification Nomination Examinationapprox. 1-2 months Review Processapprox
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Engineering or any other related field. You must meet the requirements to access and perform research on dual-use technologies according to Norwegian regulations on Control of the Export of Strategic Goods
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water