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representation in atmospheric prediction models. The initial appointment is for a term of one year but may be extended upon satisfactory performance and available funding. Job description: Using large-eddy
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: Steinberg Centre for Simulation and Interactive Learning (SCSIL) The Surgical Performance Enhancement and Robotics (SuPER) Centre in collaboration with Steinberg Centre for Simulation and Interactive
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collaboratively with other research team members, including research coordinators/assistants, graduate students, clinical residents, and post-doctoral fellows. Work Performed Assist with the operation of
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transport properties. - Operation of new instrumentation and characterization tools. - Mentor and assist in the training of undergraduate and graduate students and contribute to laboratory training activities
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conditions. Optimize the MRTOF mass spectrometer for routine operation. Advance our spatially resolved laser ablation ion sources for mass calibration and spectroscopic applications Lead the Canadian Ba
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administrative and finance staff within OVCARE. Work Performed -Leads day-to-day wet lab operations of the biobank in collaboration with the Clinical Research Manager and Data Manager on overall biobank oversight
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manuscripts, reports, knowledge mobilization products, and conference presentations; contributing to grant development (e.g. preparation of large-scale national funding applications). perform administrative and
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-and-microbubble (USMB) therapy platform. Animal procedures: Safely handle and monitor mice and/or rats and perform approved procedures, including tumour inoculation, tumour monitoring, treatment
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performance monitoring, calibration, and instrument benchmarking. Develop, optimize, and standardize experimental and imaging protocols, contributing to improved reproducibility and methodological rigor across
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: Programming proficiency in at least R or Python (ideally both), plus comfortable use of Unix/Linux shell. Hands-on experience with high-performance computing (Slurm/PBS or equivalent) and/or cloud computing