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Simon Fraser University | Northern British Columbia Fort Nelson, British Columbia | Canada | 18 days ago
at all levels—developing new materials, designing creative and interactive technologies, engineering future hardware platforms like quantum computers, and writing the algorithms that power machine learning
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self-help tools, training programs, and customer workshops to promote meaningful outcomes related to utilization of Bionano tools. Collaborate with product development teams and share critical product
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(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
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(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
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(AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of
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. Responsibilities include (but not limited to): Lead the development of the NC-ARPES technique (hardware, post-processing algorithm, theory, data interpretation) Propose and perform new TR-ARPES studies of quantum
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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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platforms like quantum computers, and writing the algorithms that power machine learning, big data analytics, and predictive modeling. Beyond technological development, SFU’s researchers also explore
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with expertise in biology, biotechnology, computer science, microscopy and bio-engineering that is developing new microscopy hardware and new computational algorithms for the encoding and decoding
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, and explainability; developing unbiased algorithms and responsible data use; addressing the social impacts of AI and IT-induced biases; equitable compensation policies; combating labour discrimination