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, applied mathematics, statistics, computer science, strong gravity, condensed matter theory, particle physics, quantum fields & strings, quantum gravity, quantum foundations, quantum Appl Deadline: 2026/01
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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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closely with researchers at McGill and partners worldwide, leveraging industry-standard tools and technologies to ensure the quality and reliability of the developed systems. Qualifications: PhD in
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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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medical physics, computer science, biomedical engineering, electrical engineering, applied mathematics, or a related field; or an MD with significant research experience and deep familiarity with AI
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and flexibility to travel to Switzerland as required MINIMUM QUALIFICATIONS: Your qualifications include a recent Ph.D. (within 5 years) in particle physics (or you are expecting to complete your PhD
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. *** A Postdoctoral fellow is a full-time student currently enrolled in a Canadian University program. The individual must have recently been awarded (within 5 years) a PhD or equivalent. The Postdoctoral
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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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: Undergraduate or entry to practice health sciences degree is required. (i.e., Bachelor of Sciences, Bachelor of Sciences in Nursing, Respiratory Therapy Advanced Diploma, etc. although equivalent experience may
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
: · PhD in Mathematical Biology, Ecological Modeling, Economics, Fisheries Science, or a related field. · Strong background in ecological and/or economic modeling, population dynamics, and quantitative