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Field
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probabilistic behavioral models for verification, performance evaluation, and optimization using model-checking techniques, ultimately bridging static system design and dynamic operational analysis. We offer
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mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems, diverse molecular techniques, and advanced imaging. The project will involve both internal and
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Type: Hybrid Eligible Sponsorship Eligibility: Not eligible for visa sponsorship Salary: Salary commensurate with education and experience Restricted: Yes Criminal Background Check: Yes About the
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determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Create a Job Match for Similar Jobs About Harvard University Harvard University is devoted
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scientists, engineers, and/or doctors! The lab is committed to fostering lifelong learners in an environment that is diverse, inclusive and respectful. Learn more about our lab here: https
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 6 days ago
experimental investigations and theoretical modelling, with a view to obtain and publish original and innovative results in leading refereed journals, present research at academic seminars and at national and
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in particular artificial intelligence (AI)—to study genetic and epigenetic alterations in cancer. ICGI is recognised for its work in digital pathology, where AI is used to develop new models
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information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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, the Department of Mathematics, and the Department of Philosophy. To respond effectively to the accelerating decline in biodiversity, BioM will unite ecology, statistics, and philosophy to improve the modelling and