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. Applicants should have expertise in the application of statistical methods in data science, machine learning, or artificial intelligence. Experience must include the preparation and delivery of course content
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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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research-intensive university. We seek candidates able to contribute to curricular development and to teach across our diverse professional (BI, MI, MMSt) and research (PhD) programs. Evidence of excellence
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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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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 14 hours ago
-disciplinary research program will align with the priority areas of ‘Body function and mobility across the health continuum’ in the Faculty of Health and ‘AI and Machine Learning’ in the Faculty
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Science, or a related field. Strong programming skills in Python, R, or related languages for data analysis and machine learning. Experience with genomics data analysis, health informatics, or computational
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). We seek candidates able to contribute to curricular development and to teach across our diverse professional (BI, MI, MMSt) and research (PhD) programs. Evidence of excellence in teaching will be
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Course description: A half-year capstone design course in which students work in small teams to apply the engineering design, technical, and communication skills learned previously, while refining
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to teach and conduct research on all aspects of the workplace and employment relationships. The CIRHR faculty reflect the depth, breadth, and diversity of our university. The CIRHR is located in a historic
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selected as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016, 2017 and 2018. To learn more about our work environment, colleagues, leaders, students and innovative