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exceptional postdoctoral research fellows interested in developing deep learning and computational methods for pathology image analysis, multimodal data integration, and other medical modalities (e.g
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and implement innovative image analysis methods to quantify plant characteristics. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and
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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Outstanding Postdoctoral Training Strategy
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: Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing priorities and work demands. Teamwork: Ability to work collaboratively with others and contribute to a
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, analysis, and optimization. The goal of the project is to develop methods for the synthesis and analysis of systems producing renewable fuels and chemicals; and use these methods, in collaboration with other
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to develop applied research skills in machine learning, interact with an international network of collaborators, and gain post-doctoral research experience. The ideal candidate is self-motivated and can work
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 4 days ago
. For those interested, there is also an option to learn and use in vivo cancer or diabetes models. Collaborative and Supportive Environment: You will collaborate closely with experienced scientists and
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into concrete observational and computational strategies. This work will be carried out under the supervision of Professor Alessandra Corsi, in close connection with collaborators at the JHU’s Institute for Data
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wide variety of backgrounds learn from one another, share ideas, and work collaboratively. UCC is committed to being an employer that recognises the value of diversity amongst its staff. We encourage