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Field
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allows for translation of novel methods to our cancer clinics in Canada (Vancouver, Victoria, and Kelowna) and beyond. Requirements: The ideal candidate will have a PhD in computational modeling/oncology
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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-doctoral researcher with a strong quantitative background in biology, evolution, or social science, and previous experience in mathematical modeling or behavioral experimentation. Purpose: Complete a multi
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; environmental science; statistics; mathematics; data science; data visualization; documentation; records management; complex problem solving; critical thinking; resource management; communication; community
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/GNC systems has traditionally relied on model-based techniques, which in turn, have their foundations in a solid body of mathematical proofs (such as guarantees of stability and robustness
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techniques including deep neural networks and large language models (such as GPTs), with state-of-the-art functional genomics approaches, including crop genomics, genome editing, and single cell multiomics
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research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results
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, Applied Mathematics, Statistics or related computational field. Superb quantitative background, strong coding skills (e.g., Python, R). Expertise in infectious disease modeling. Strong record of peer
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to disseminate research results QUALIFICATIONS Applicants must have (or be about to receive) a PhD in physics, biophysics, systems biology, applied mathematics, bioengineering, chemistry, chemical engineering, or
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within