61 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" Fellowship positions at University of British Columbia in Canada
Sort by
Refine Your Search
-
enhance provincial capacity to tailor care approaches in response to the ongoing substance use crisis. The ideal candidate will have a passion for integrating multiple sources of quantitative data and a
-
. Paragenesis and vein evolution – developing a detailed framework linking vein formation to magmatic and hydrothermal activity. Structural controls on gold mineralisation – mapping and analysing vein networks
-
documentation. Develops integrative models of radiation response through the combination of genotype and biomarker data. (Raman, blood marker etc.) Facilitates processes for data transfer and collaboration by
-
the development of excellent doctoral and postdoctoral training programmes and collaborative research projects worldwide. By doing so, they achieve a structuring impact on higher education institutions, research
-
. 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
-
developed for a range of important brain disorders, including neurodegenerative dementias, movement disorders and neuroinflammatory diseases such as multiple sclerosis, epilepsy and neuropsychiatric
-
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
-
Translating basic science discoveries into practice Improving techniques to measure pain Developing new and more personalized treatment approaches Alternative approaches to pain management including research
-
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
-
. This role focuses on developing and applying AI and deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects