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for this position will have the following qualifications/qualities A PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in
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the Université Paris-Saclay, France and scientific director of the Clinicobiome programme at Gustave Roussy in the Paris suburb of Villejuif. The aim of this medical research programme is to examine how microbiota
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students. We are a cohesive Faculty committed to internationally-oriented, interdisciplinary research of high societal relevance with our new research programme Transformations, Communities, and Environments
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computational approaches combined with experimental validation to investigate how these genomes get shaped and which proteins are involved in this fundamental process. As a postdoc, you will contribute
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computing; Experience with process-based modeling or willingness to learn; Hands-on experience in conducting controlled experiments, especially in soil or microbial systems Demonstrate excellent level of
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to pharmacy, from neurosciences to computer science, and from molecular and evolutionary biology to marine biology. Our researchers pursue fundamental key questions while collaborating with partners from
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our new research programme Transformations, Communities, and Environments (TRACE), which encompasses socio-spatial transformations; wellbeing, equity, and resilience for people and places; and socio
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Organisation Job description Project: Diabetes2Care A Personalized Lifestyle Intervention for People with Diabetes Project description Type 2 diabetes has a high prevalence in The Netherlands. Due to the high numbers of people that are affected, it is difficult to find sufficient support....
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Project on Smart Beds for Obstructive Sleep Apnea for Individualized Diagnosis, Treatment, and Follow Up Project description Obstructive sleep apnea (OSA) affects about 1 billion people worldwide. OSA is characterized by a repetitive collapse or narrowing of the upper airway during sleep...
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relevant discipline (e.g., data science, computer science, engineering science, artificial intelligence, or health science/psychology with specialization or additional training in data science); Demonstrable