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. Nunez’s lab focuses on the use of AI in mental health and cancer care, and the Postdoctoral Fellow will join a multidisciplinary team composed of data scientists, software engineers, and medical trainees
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to be integrated with other sequence-based omics technologies. We are looking for two postdocs to establish this new technology as a new metabolomics platform — this is an exciting project that combines
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Intrusion-Related Gold Systems (RIRGS) in the Yukon Territory. The project investigates the structural, magmatic, and mineralogical controls on gold mineralisation at a significant new RIRGS deposit. Project
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of virtual care services and usage of digital health technologies for patient care. The research seeks to evaluate how technology-enabled health services can improve access to healthcare. With access
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on Science, Technology and Innovation between France and Canada in 2023. The call for applications is open to the following themes: Emerging Technologies: AI, quantum, etc. Health: One health, public health
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Department: Mechanical, Industrial and Mechatronics Engineering Position supervisor: Dr. Farrokh Janabi-Sharifi Contract length: 1 year Hours of work per week: 36.25 Position type: Postdoctoral
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Nature Careers | Government of Canada Ottawa and Gatineau offices, Ontario | Canada | about 1 month ago
-Guided Materials Development for Tomographic Volumetric Additive Manufacturing (TVAM) The Prediction of Structure-borne Sound in Sustainable Low Carbon Building Constructions ALMA Archival Research
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the development of excellent doctoral and postdoctoral training programmes and collaborative research projects worldwide. By doing so, they achieve a structuring impact on higher education institutions, research
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applicants who receive their PhD less than one year prior to their start date. Fellows from a diversity of disciplines — from groups who have traditionally been underrepresented in science, technology
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initiative that will advance our understanding of how genetic factors influence cardiac structure and function, and yield AI models that link phenotypic findings with genetic data to predict CVD risk and