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Field
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experience of the candidate 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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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning
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related to the preparation for a career in research or academia, participate in the University’s Individual Development Plan policy for postdoctoral scholars, have a PhD or equivalent terminal degree
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tunnel experiments is a plus • Experience in programming and AI/machine learning is a plus More Information Location: Kent Ridge Campus Organization: College of Design and Engineering Department
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excellent interpersonal skills. About You You will hold a PhD in a relevant subject such as Aerospace, Mechanical, Electrical, or Software Engineering for the Research Fellow position, or hold a Master's
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undergraduate programs (BS through PhD). The College has seven academic programs that are externally accredited and is home to more than 1,900 undergraduate and 950 graduate students and approximately 140 faculty
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Health Regulations. Assist in project resource requirements and managing student projects. Job Requirements: Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering or equivalent
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily