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on the Posting End Date. Job End Date September 30, 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
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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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Learning Course Description: Machine Learning applications are increasingly utilized to make crucial decisions in many sectors of our economy and society. These include, but are not limited to, healthcare
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: Current Students in an Undergraduate Program, Current Students in a Master’s Program, Current Students in a PhD Program. Cover letters are mandatory. Please submit it along with your resume. At UBC, we
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emerging technologies such as machine learning and artificial intelligence. In addition, the ideal applicant will have excellent communication skills and have demonstrated capacity and aptitude for effective
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Sciences, Machine Learning, Mathematics, or a related field—or equivalent qualifications and demonstrated expertise in generative AI. Work Experience: Training in the following areas: Experience: Minimum
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 8 hours ago
metabolomics] research, with experience in the use of techniques in machine learning, statistics, algorithm engineering, bioinformatics, or advanced data visualization. Evidence of effective participation and
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, research areas include Operations Research, Information Engineering, Human Factors, and Applied Machine Learning, all of which seek to improve the systems we as humans rely on to navigate our world
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experience in optimization, machine learning, control systems, or robotics is desirable. No other specific qualifications beyond and a willingness to learn within an interdisciplinary team. If you have any
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for this position are as follows: PhD in Forest Ecology, Entomology, or a closely related field, with a focus on geospatial modeling, invasive species dynamics, and applied machine learning for pest risk assessment