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This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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fundamental and applied research in different areas of Human-Computer Interaction (HCI) such as visualization, human-centered design, privacy, graphical design, and human-centered AI. We are looking
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sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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at least 1 million DNA barcodes. The project involves collaboration with a computer vision lab at Linköping University, focused on developing AI-assisted techniques for picking out specimens for genome
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, and agent-based modelling have paved the way for innovative collaborations between social scientists and computer scientists that jointly seek to answer fundamental questions of the social sciences and
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computer. The WACQT team at Chalmers currently has about 100 members (faculty, permanent research staff, postdoctoral researchers, PhD students, and undergraduate students). WACQT is committed to promoting
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measurements, vegetation inventory and biodiversity assessments for a set of diverse continuous cover forestry systems in boreal Sweden. The project will develop bottom-up estimates of the forest ecosystem