20 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at University of British Columbia in Canada
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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Staff - Non Union Job Category M&P - AAPS Job Profile AAPS Salaried - Scientific Eng., Level A Job Title Machine Learning Engineer/Scientist Department Bashashati Laboratory | School of Biomedical
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, nonparametric modelling, sampling and data collection, spatial and temporal data analysis, statistical finance, or unsupervised/semi-supervised machine learning. The candidate will be expected to teach and
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diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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to the successful pursuit 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
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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 students. Our commitment to employment equity helps
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to the successful pursuit 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
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sciences.Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Proposals that include deep or machine learning
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that incorporate artificial intelligence and machine learning or climate change and human health are of particular interest. BWF believes that a diverse scientific workforce is essential to the process and