38 data "https:" "https:" "https:" "https:" "Brunel University London" Postdoctoral research jobs at Aarhus University
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of Sensory & Consumer Science studies, qualitative and quantitative data collection and -analysis as well as manuscript writing is requested. The candidate is expected to undertake data collection
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: https://ece.au.dk What we offer The Department of Electrical and Computer Engineering offers: An exciting opportunity to work on cutting-edge research in IoT systems and critical infrastructure monitoring
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international research network and good industrial and professional collaboration. Please refer to Department of Animal and Veterinary Sciences (au.dk) for further information about the department: https
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. Experimental execution from development to data analysis and interpretation. Collaboration with Clinical and Research Partners. Provide mentorship to junior researchers within the project. Drive your own
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sets, lexicon development, use of instrumental techniques to correlate or predict sensory characteristics and multivariate data analysis. This position is part of an interdisciplinary research project
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? Then the Department of Electrical and Computer Engineering invites you to apply for a 2 year postdoc position bridging research with industrial implementation and innovation. Expected start date and
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description We invite applications for a 2-year postdoctoral position with the possibility of extension. The successful candidate will lead experimental campaigns and data analysis to quantify greenhouse gas
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reactors Maintain detailed records of experimental data, process conditions, and system modifications. Publish scientific articles based on data collected during the research, development, and innovation
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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
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals