187 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Canada
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The University of Toronto is pleased to announce the third call for applications for theEric and Wendy Schmidt AI in Science Postdoctoral Fellowship , a program of Schmidt Sciences, which brings
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collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
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development and target discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by
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to collaborative efforts aligned with translational and commercial development goals, including work supported by the CIFAR Multiscale Human Program and UBC’s Biodevice Foundry. Qualifications PhD in immunology
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discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by the time of
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Human Program and UBC’s Biodevice Foundry. Qualifications PhD in immunology, developmental biology (focused on the immune system), immune-engineering, or a related field (obtained within the last 5 years
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environments (namely the Surrey Memorial Hospital NICU-partnering with Ronald MacDonald House). There would be opportunities to work closely with experts and students in the fields of human-computer interaction
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set the research direction and computational approach to the data. Qualifications: - PhD in Biology, Bioinformatics, Computer Science, Statistics or a related quantitative field. - Experience working
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The Japan Society for the Promotion of Science (JSPS) has established the JSPS Postdoctoral Fellowships for Research in Japan – Short-term program. A limited number of promising early career
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The Japan Society for the Promotion of Science (JSPS) has established the JSPS Postdoctoral Fellowships for Research in Japan – Standard program. A limited number of promising early career