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applying and developing deep learning models (e.g. CNNs, ViTs, or geometric deep learning) Proficiency in Python and PyTorch Motivation to work with interdisciplinary clinical partners A track record of
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, or similar) and data analysis. Familiarity with heat pump systems, building energy simulations, or control/optimization is an advantage. Track record of scientific publications in relevant fields (thermal
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physiological processes as accurately as possible by using, for example, skin conductance, heart rate variations, eye-tracking techniques, and other physiological measures. Such measurements may provide insights
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to the project topic, and have a demonstrated track record of scientific and/or applied research publications. Ideally, you have knowledge of Northwestern European plant species and a solid understanding of
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, transparency or confidentiality rules are a plus); Proven knowledge in the EU regulatory framework pertaining to digital technology and data. Excellent research skills demonstrated by a track record of
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experts and in alignment with ongoing initiatives within the Agency. Your objectives will be to perform independent research and development, targeting one or more of the following key areas, subject to
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PyTorch. Track record of publishing in top Vision/Graphics/Animation and Human-Computer Interaction conferences/journals such as CVPR, ICCV, ICMI, SIGGRAPH, or similar conferences/journals. Strong
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PyTorch. Track record of publishing in top Vision/Graphics/Animation and Human-Computer Interaction conferences/journals such as CVPR, ICCV, ICMI, SIGGRAPH, or similar conferences/journals. Strong
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computational methods for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more