189 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" research jobs in Canada
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inverse modeling methods, machine learning, and artificial intelligence techniques. Appointment Details: Start date: As early as March 1, 2026. Annual Salary: $55,000 Application review: Ongoing until
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, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary
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of required background checks. At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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December 10, 2026 At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and
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package valued at $175,000 in the first year and $102,000 in the second year, which includes a salary, research budget, housing allowance, space and more. Learn more about benefits and perks here . Runway
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knowledge in one or more areas and be enthusiastic to new learning opportunities. Key Responsibilities: The position is responsible for design and implementation of prototypes, electronic control, data
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of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and
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diversity and representation at all levels of teaching, learning and research. Nominees must be nominated by their prospective Faculties/divisions following the timeline and processes outlined below. While
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sciences, and the arts. Fellows of the College for Life Sciences are invited to become part of this “learning community”. Our goal is to promote a kind of science that transcends disciplinary boundaries and