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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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imaging QUALIFICATIONS Successful applicants will have: a PhD in medical physics, computer science, biomedical engineering, electrical engineering, applied mathematics, or a related field; or an MD with
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and damage to neurons, and the major cause of permanent disability in multiple sclerosis (MS) and other neurological diseases. Using the latest in computer modeling, molecular and imaging technology, we
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Qualifications: PhD in Chemistry Before applying, please note that to work at McGill University, you must be both authorized to work in Canada and willing to work in the province of Quebec at the campus where
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, and inclusion Preferred Qualifications Graduate degree (PhD or equivalent) in relevant discipline or completion of a technical program and a minimum five years of related experience or an equivalent
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environment allows for translation of novel methods to our cancer clinics in Canada (Vancouver, Victoria, and Kelowna) and beyond. Requirements: The ideal candidate will have a PhD in computational modeling
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, Victoria, and Kelowna) and beyond. Requirements: The ideal candidate will have a PhD in computational modeling/oncology, systems biology, applied mathematics, nuclear medicine physics, or a related field
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have a PhD in computational modeling/oncology, systems biology, applied mathematics, nuclear medicine physics, or a related field. Prior experience in at least one of the following is a requirement
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additional internal guidelines, procedures, or deadlines in place for this fellowship opportunity. The Canada Postdoctoral Research Award (CPRA) program recognizes and supports the next generation of
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | 2 months ago
. Eric Rapaport and his team are now seeking applications for a two-year Postdoctoral Fellowship in a research program called A data-driven geospatial planning tool: understanding cumulative climate risks