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Field
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or psychological interventions for patients with vulvar and sexual health concerns or (2) conduct a sexual psychophysiology study using blood flow imaging technology. As part of Dr. Bouchard’s lab, the Fellow will
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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. computational pathology, genomics, transcriptomics and medical imaging. Experience with containerisation and orchestration tools such as Docker, Singularity and Kubernetes. Exposure to MLOps frameworks (e.g
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techniques include motor/behavioral tests of mice, in vivo compound administration, postmortem tissue harvesting and processing with a focus on the nervous system, cell tracing, immunohistochemistry, mouse
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, clinicians and imaging experts from UBC, BCCRI, and our international institutional and industry partners. The fellow will work within our multidisciplinary team (medical physicists, engineers, nuclear
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. Prior experience in at least one of the following is a requirement: physiologically based pharmacokinetic (PBPK) modeling, computational oncology/biology, kinetic modeling, advanced image processing
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collaboration with researchers, clinicians and imaging experts from UBC, BCCRI, and our international institutional and industry partners. The fellow will work within our multidisciplinary team (medical