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vision, machine learning, deep learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics. Experience in deep learning, computer vision, or neural
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Science, Planning, Remote Sensing, GIScience, Computer Science, Statistics or a related discipline; (b) preferably have at least two years of postdoctoral research experience; (c) have strong
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independently. Merits: Education or training in computer vision, machine learning, deep learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics
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learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics. Experience in deep learning, computer vision, or neural network development. Experience with
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
Biology, Bioinformatics, Computer Science, Applied Mathematics, Statistics, Biophysics, Biomedical Engineering, or a related field. Strong programming skills in at least one of: Python, R, C/C++, or Perl
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! Education · PhD in computer science, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods
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fundamental AI methods together with their software implementations for interpretable statistical fault prediction and lifetime assessment in the context of Structural Health Monitoring of operating wind
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Mathematics and Mathematical Statistics at Umeå University is opening a PhD position in
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of Religion at the Department for the Study of Religions in the position of a postdoctoral researcher focusing on mathematical modelling of data and statistics within the Czech Science Foundation Junior Star
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. The PhD will adopt a strongly quantitative and data-driven approach. The student will develop and evaluate mathematical and statistical models of short-term attention dynamics, drawing on tools from