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University of Toronto - Dept. of Chemical Engineering & Applied Chemistry | Central Toronto (Roselawn), Ontario | Canada | 6 days ago
historically and are ongoing, we strongly welcome and encourage candidates from those communities to apply. Areas of interest include, but are not limited to, biomolecular engineering; enzyme and protein
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looking for a Postdoctoral Researcher to lead a project on the development and scale-up of enzyme-powered nanomotors, with a focus on translational development toward clinical and industrial application
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include: Conduct molecular cloning, plasmid construction, and DNA assembly using PCR, Gibson assembly, restriction enzyme cloning, bacterial transformation, and sequence verification. Perform recombinant
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problems in the life sciences including but not limited to those relating to nucleic acid structure/function, proteomics, molecular microbiology, protein structure and function, and enzyme kinetics. The
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focus on synthesis and evaluation of pathogen-selective, enzyme-activated carrier chemistry and will work closely with computational collaborators and other team members on iterative design
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biochemical techniques; (2) resolve the structural basis of enzyme cooperation using biophysical tools, X-ray crystallography, and cryo-EM. This project will deliver the first complete biochemical and
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health and neuroinflammation. For more information on my research background and publications, please visit my ORCID profile: https://orcid.org/0000-0002-7691-8948 . Responsibilities: Perform Middle
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welcome and encourage candidates from those communities to apply. Areas of interest include, but are not limited to, biomolecular engineering; enzyme and protein engineering; metabolic engineering
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functional methane monooxygenase (MMO) enzymes, including particulate and soluble MMO, and investigate strategies to improve enzyme expression, assembly, stability and activity in planta . The post
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mycorrhizal fungal interactions and functioning, use of stable isotopes and enzyme assays Experience in analysis and interpretation of experimental data, including statistical analyses of large datasets