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: simulation and risk modelling using advanced statistical and machine learning based methods. strategic portfolio management and dependency structure modelling for financial assets. effects of climate change
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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working model that combines remote working with on-site work, according to organizational needs and the nature of the tasks involved. About the UOC A leader in e-learning, our pioneering university is a
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strong understanding of computer hardware or VLSI design. The selected candidates will contribute to the development of: A Physical-to-Electrical Abstraction and Modeling Engine A Circuit-Level Abstraction
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balance fails in disease or injury and how it might be restored. For more information on our research interests, please visit https://www.zhulab.fish The lab uses larval zebrafish as a tractable and
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. Research in the lab is highly multidisciplinary and quantitative, requiring development and use of cutting edge computational modeling and statistical analyses (including machine learning and artificial
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Mathematics, or a related field A strong background in image/signal processing, particularly in computer vision. Strong programming skills and experience with at least one deep learning framework e.g
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, behavioral economics, and machine learning, to help policymakers identify and generate evidence on innovative approaches and policy solutions to their most pressing environmental and energy challenges. Job
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Engineering, Biomechanics, Computer Science, or related field Preferred Experience: Experience with machine learning in medical imaging/biomechanics; grant writing support; clinical gait analysis in clinical