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working with Environment Canada to build better species distribution models that include species interactions and connectivity. The postdoc will develop professionally by learning new statistical techniques
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or biomedical engineering or a related field. Strong programming skills, particularly in MATLAB or Python for analyses of neural signals are strong assets Previous experience with animal models using
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 5 days ago
, deadline-driven settings. Strong interpersonal skills with the ability to collaborate effectively in a team environment. Desirable Experience in cell and molecular biology Experience in tissue culture and
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 2 days ago
design an optical system that can be easily built and used by non-expert users. The applicant will work closely with the inventors of RAP technology and a group of academic and industry collaborators
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autonomic research. A position is open for a postdoctoral fellow with a PhD in neuroscience, biomedical engineering, or a related discipline, and a strong interest in neuroscience, cardiovascular and vascular
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neuroscience and optionally molecular biology and data science. We are looking for a candidate that is driven, can leverage the lab’s existing expertise and build upon this and does not shy away from new ideas
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collaborate with early career researchers, Northern partners including Indigenous communities, and international experts to analyze data and integrate findings into broader ecological models, enhancing our
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statistical modeling approaches. Support the integration of implementation science methods to improve the translation of research findings into clinical practice. Assist in the development of guidelines and
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to the role of an Alzheimer’s disease susceptibility factor, CD33, in disease pathogenesis, as well as development of novel CD33-based therapeutics in this context (PMID:35940942). Transgenic models (PMID
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management.•Primary knowledge areas include wildfire ecology, forest ecology, disturbance ecology, remote sensing, silviculture, and habitat modelling.•The PDF will work with a team to develop data layers and