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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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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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large international network. Furthermore, we collaborate extensively with other groups, including both clinical and basic pharmacology researchers as well as environmental medicine specialists
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
, networking and social activities. a workplace characterised by professionalism, equality and a healthy work-life balance. Place of work and area of employment The place of work is Helsingforsgade 10, 8200
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a focus on mentoring and individual career development. Training in state-of-the-art technologies and data analysis as well as research management, oral and written communication, and networking
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of publications in high-ranking international peer-reviewed journals Contribute to public dissemination of policy and management relevant knowledge Participate in network building activities both internationally
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, innovation, and critical thinking across fields. A collegial and inclusive workplace with networking activities, knowledge sharing, and a commitment to team development. A strong focus on professionalism
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aspects of drug use, drug effects, and drug safety. The group is highly regarded within pharmacoepidemiology and has a large international network. Furthermore, we collaborate extensively with other groups
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine research sections with
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and