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Nature Careers | Northern British Columbia Fort Nelson, British Columbia | Canada | about 2 months ago
of the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). We are seeking scientists to lead research projects with a specific focus on the genetic determinants of severe adverse drug and vaccine reactions
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. Although this approach has led to the development of alloys such as Type 316, Alloy 617, 800H, and 709, the process remains slow, expensive, and inefficient. Creep-fatigue represents a complex interplay of
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Complex Systems. Applicants are invited to propose a research project around understanding the impact of regenerative design interventions in complex industrial systems, particularly food systems
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verbal communication skills. • Experience in teaching relevant subjects to university students. • Able to communicate complex and conceptual ideas to a range of groups. • Able to balance the pressures
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of the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). We are seeking scientists to lead research projects with a specific focus on the genetic determinants of severe adverse drug and vaccine reactions
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laboratory of Dr. Bruce Carleton and the multi-centre research team of the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). We are seeking scientists to lead research projects with a specific focus
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analogous processes in more complex human cellular systems. The research aims to establish mechanistic understanding of molecular networks that maintain homeostasis under stress conditions. Through rigorous
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and the multi-centre research team of the Canadian Pharmacogenomics Network for Drug Safety (CPNDS). We are seeking scientists to lead research projects with a specific focus on the genetic determinants
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conduct original, foundational and applied research on the application of Quantum timing devices to networked radar systems and to evaluate their feasibility and performance limits through a combination of
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science and artificial intelligence concepts and tools to solve complex problems. Candidates will also be developing machine learning techniques and applying them at scale to specific projects with regular