69 algorithm-development-"Multiple"-"Prof"-"UNIS"-"DIFFER" Fellowship positions in Canada
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: Apply Position Description We invite applications for multiple postdoctoral fellowship applications at the Trotter Space Institute at McGill University (TSI). TSI is an interdisciplinary research centre
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position under the supervision of Dr. Adam Shlien at the Hospital for Sick Children (SickKids), in downtown Toronto, named as the world's best pediatric hospital. The project involves the development of new
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Fellow in Artificial Intelligence and Indigenous Knowledge for its research “pod” in Toronto, Canada. Abundant Intelligences conceptualizes, designs, develops, and deploys Artificial Intelligence based
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research and development. Here, you can apply your engineering talent to develop new life-saving technologies – for example, medical imaging, wearable devices, surgical robotics and laboratory-grown tissues
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the opportunity to work on innovative research projects alongside expert researchers while developing their career. Areas of research include: Ionizing Radiation Standards Plant Regeneration through
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. This initiative aims to develop highly skilled researchers advancing knowledge and improving outcomes for individuals affected by stroke-related cognitive decline. The fellowship fosters innovative research
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developed for a range of important brain disorders, including neurodegenerative dementias, movement disorders and neuroinflammatory diseases such as multiple sclerosis, epilepsy and neuropsychiatric
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Applications. • January 15 – March 1st: Applicants seek endorsement from host institution to apply, prepare and submit application. • March 15: Deadline for Application. • June 15th: Notice of Decision
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other co-morbidities. The exciting next stage of this program will be to expand to multiple countries in East and West Africa, with rigorous evaluation. We are looking for an individual with a desire to
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cardiac precision medicine through artificial intelligence and machine learning. The postdoctoral fellow will contribute to the development of a comprehensive, multi-modal framework for predicting and