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experience with deep learning frameworks (e.g., PyTorch) Experience in working with time-series data Good understanding of Internet of Things, wireless communication network and systems Strong publication
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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working relationships, networking and social activities characterized by professionalism and equality. Aarhus University offers a good work-life balance. English is spoken widely, even if Danish is the main
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lively, open and critical discussion within and across different fields of research a work environment with close working relationships, networking and social activities a workplace characterised by
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industrial collaborators A work environment with close working relationships, networking and social activities Opportunities for career development Place of work and area of employment The place of work is
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collaborators a research climate encouraging lively, open and critical discussion within and across different fields of research a work environment with close working relationships, networking and social
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
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national and international research networks time spent abroad working at one or more internationally recognised research institutions. Finally, applicants are asked to provide a proposal for research to be
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fresh perspective on how specialized brain networks can identify and categorize causes of sensory inputs, integrate information with other networks, and adapt to new stimuli. It proposes that perception
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connection to the research environment, and a comprehensive national and international research network and good industrial and professional collaboration. Please refer to Department of Animal and Veterinary