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investments of over $22M in infrastructure and operation funding by TMU, the successful candidate will join a rapidly growing ecosystem focused on Medical Imaging and Therapy involving the Greater Toronto
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. Integration of Artificial Intelligence and Remote Sensing Science: machine-learning / automated analysis of large datasets, calibration and validation, feature extraction, image processing and classification
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+ Research Chair recruitment is a multi-stage process. Applicants first apply to a nomination posting at the institution. Selected nominees will then work in close partnership with Queen’s to apply to the 2026
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knowledge research. The successful candidate will have access to advanced imaging facilities within the Centre for Functional and Metabolic Mapping (CFMM) at Western’s Robarts Research Institute . The CFMM
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, organismal, or systems-level immunology, including in vivo models, advanced imaging, single-cell or multi-omics methods, or computational immunology. The successful candidate will be expected to establish
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the continuum from discovery to first-in-human trials. Successful candidates will join recent faculty hires across multiple departments with expertise in bioinformatics, biotherapeutics, imaging, inflammation
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close collaboration with industry in areas such as biomedical engineering, medical imaging, automation and systems, energy and power grids, microelectronics, microwave systems, telecommunications systems
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associates; and (b) working with students/post-docs to prepare scientific manuscripts, grant applications, and/or drafts of patent applications. Salary will be commensurate with qualifications and experience
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the implementation of novel systems or computational methodologies to obtain an understanding of how systemic or local metabolic processes impact tumour biology. Areas of potential focus would include, but not be
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Mathematics or a related field and a preferred minimum of three years post-doctoral experience. The candidate must have skills necessary for research excellence and impact in computational modelling