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that the research efforts are well directed and harmonized, our time and financial resources are utilized optimally, regulatory compliance in our research and data management are maintained at the highest level. This
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unparalleled opportunities in teaching, scholarship, clinical practice, and multidisciplinary collaboration. Innovative academic offerings include bachelor’s, master’s, post-master’s certificate, DNP, and PhD
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energy by exploring fundamentally the controversy regarding the abnormal evaporation rate and simulate/ predict vapor production rate to guide the design of an optimized interfacial evaporator. Develop
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coordination with the relevant Innovation Managers. Optimize resource allocation by identifying non-exploitable or low-strategic-value assets and proposing portfolio rationalization actions. Provide support on
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manual (e.g., electronic laboratory notebook like LabArchives), etc. to laboratory instructors); Work with prep personnel and the department Instrument Specialist to insure optimal equipment and instrument
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them to optimize any results, working to obtain new tool compounds and drug candidates. Leveraging state-of-the-art computational methods, including structure-based ultra-large virtual screenings
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personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its future ability to respond to diseases. Why
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the application. The University of Toronto requires that the successful candidate must have a PhD. The successful candidate will lead a stellar program of research with a focus on optimizing outcomes for children
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differentiation state, drug response, and resistance phenotypes. Assay Development and Screening (35%) • Design, optimize, and validate cell-based assays to support compound testing and mechanistic studies
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coefficient, temperature range, and others will be simulated to assess their impact on the thermal expansion coefficient of the composites and on the locally induced stresses. WP4: Optimal small-scale sample