11 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at McGill University
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | about 20 hours ago
addresses these fundamental challenges by employing single-molecule fluorescence microscopy to visualize mRNAs in their cellular context. Coupling these techniques with genetic and molecular biology
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We invite applications for a 1-year, full-time postdoctoral fellowship (non-renewable). This is an exciting opportunity for a dynamic, impact-driven scholar committed to reimagining global readiness
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, as well as the broader sociopolitical dynamics of legal empowerment, marginalization, and systemic inequality. Working in close collaboration with the Access to Justice stakeholders (Justice
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to understand the needs, experiences and challenges of people with rare musculosleketal conditions. Conduct quantitative analysis on functional outcomes for descriptive and modelling purposes. Partner with
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: Synthesize small molecules, produce samples of proteins and nucleic acids Characterization using a variety of biophysical methods including in silico modeling, ITC and UV-Vis spectroscopy Perform medicinal
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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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geospatial modelling of agricultural management practices across Canada, particularly those related to fertilizer use and cropping practices. As part of this, the postdoctoral researcher will contribute
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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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are available A CV detailing your academic accomplishments A copy of one relevant publication The names and contact information of two potential referees (e.g., current and former research supervisors
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: - To lead the computational part of a collaborative project on AI-assisted design of OPVs - To become knowledgeable in the field of OPVs and the relevant simulations - To learn relevant machine learning