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networks of nodes and parameters. This practice-based PhD investigates how AI can assist at the level of tool production by drafting procedural networks that the experienced technical artist can inspect
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are seeking a PhD candidate to join our young team (Computational Systems Medicine) within the context of the BMFTR-funded DIASyM (https://diasym.mscoresys.de/ ) project, to develop new statistical and
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reinforcement learning (RL), active learning, Bayesian decision theory, and stochastic optimisation for partially observed and evolving systems. Key research directions include: adaptive data acquisition
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of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim or http://github.com
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. The division is an important part of the eSSENCE e-science collaboration and of the Science for Life Laboratory (SciLifeLab ) network, a national research infrastructure for life sciences. The successful
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Leaders program, nominees must have been working and residing outside Canada when the Eddie Goldenberg Research Chairs of Canada award (https://www.canada.ca/en/impact-pluschairs.html) is formally accepted
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of Materials Design and Innovation Posting Number R260134 Posting Link https://www.ubjobs.buffalo.edu/postings/64174 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term
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enjoys a wide network of strong international collaborators all around the world, for example at the University of Oxford, the University of Melbourne, and the University of California, Los Angeles. We
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Website https://job-boards.eu.greenhouse.io/constructorknowledgelabs/jobs/4976717101 Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Required
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of Bayesian approaches such as Gaussian process regression, particle filters, Bayesian networks, graph-based approaches. Probabilistic -based uncertainty quantification is also essential. Support the design