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Field
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive
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softness with mechanical performance. Compliant mechanisms, particularly spatial compliant shell mechanisms, offer a promising solution. These structures can achieve large, controlled deformations while
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preclinical in vivo animal models? Then this position might be perfect for you! Join us! We are looking for a highly qualified and motivated PhD candidate to conduct research activities aimed at unravelling
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framework exploiting the use of physical and geometrical conservation laws in a variety of spatial discretisation schemes (i.e. Finite Element, Finite Volume, Meshless). The resulting conservation-type
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Ecole Polytechnique Federale de Lausanne, Unsteady Flow Diagnostics Laboratory Position ID: Ecole Polytechnique Federale de Lausanne -Unsteady Flow Diagnostics Laboratory -PHD [#30284] Position
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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analytical skills for model formulation and optimization Demonstrated research potential, ideally with a track record of publications in relevant venues (journals such as IEEE T-ITS, INFORMS Transportation
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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Job Description We are looking for a motivated PhD candidate to explore how fish distribution and habitats are linked across coastal and offshore waters in Denmark. The project focuses on improving
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depression and the role of the endocannabinoid system? Do you enjoy working in a lab with preclinical in vivo animal models? Then this position might be perfect for you! Join us! We are looking for a highly