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Job Description The SIGNATURE project aims to define the human insulin resistance molecular network by identifying different baseline sub-phenotypes of insulin resistance in humans and assessing
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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supportive, dynamic and ambitious research environment with a strong scientific and social network for postdoctoral fellows and good mentoring opportunities. Furthermore, you will have access to state
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of Denmark. The position is part of a larger EU project entitled “FEDORA - Federation of network optimisation services, simulation foresights, and data alchemy for adaptable, agile, secure, and resilient
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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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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
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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
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. CFA is currently studying how the model influence research-industry collaboration in two programs, Plant2Food and ODIN (Open Innovation Discovery Network) . As part of a small interdisciplinary project
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and data analysis as well as research management, oral and written communication, and networking. Participation to international conferences to facilitate successful integration into the cilia research
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interdisciplinary environment with many national, international collaborators; a working climate that invites lively, open, and critical discussion; a working environment with close working relationships, networking