185 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Canada
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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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, reports, and scientific publications Learn and apply pharmacokinetic/pharmacodynamic (PK/PD) analysis techniques to interpret drug assay data Train junior laboratory members Qualifications The successful
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study design Review analytical data and prepare protocols, reports, and scientific publications Learn and apply pharmacokinetic/pharmacodynamic (PK/PD) analysis techniques to interpret drug assay data
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to prevent pediatric mortality and morbidity, enabled through digital health technologies in Africa (Kenya, Uganda + more). The Trainee will be working on a program with over 15+ years (Smart Discharges
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Overview On this page Description The Postdoctoral Fellowships (PDF) program provides support to a core of the most promising researchers at a pivotal time in their careers. The fellowships
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of their programs. MA and PhD students may hold a CSRS fellowship only once during each degree program. Applicants may apply for fellowships at other centres at the university; however, because this fellowship
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, StrokeCog can leverage CANTRAIN’s online tools, learning-management systems, training programs and its college of mentors. Applicants apply to the StrokeCog fellowship program through the CANTRAIN portal
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of data, creating diverse training opportunities. Interested applicants should have a PhD in biology, molecular biology, biomedical engineering, biotechnology, materials science, computer