-
involved in development of PET acquisition/analysis approaches. Maintain a strong collaboration with the imaging infrastructure manufacturers in the preclinical MRI and PET sector. Collaborate seamlessly
-
experience in genomic and image data analysis to play a key research role in the bioinformatics analysis of computational genomic research data, applied to translational oncology and drug development
-
activation, and neuroimmune communication. Apply advanced microscopy techniques including confocal microscopy, live-cell imaging, high-content imaging, and three-dimensional image analysis. Perform and
-
Software and AI Research Assistant with experience in machine learning and medical imaging. This position entails performing research and analysis, conducting analyses, assisting researchers and principal
-
Lunenfeld-Tanenbaum Research Institute | Central Toronto Roselawn, Ontario | Canada | about 21 hours ago
methodologies across both areas of interest may include, but are not limited to: hypothesis-driven mechanistic studies; the generation and analysis of large-scale multi-omic datasets (including single-cell
-
culture, fluorescence confocal microscopy, transmission electron microscopy, digital image analysis and statistics. The capacity to thrive in a highly collaborative research laboratory environment is
-
Associate Professor/Professor -JDMI UHN Chair in Medical Imaging and AI at the University of Toronto
on projects involving analysis of medical images. If a practicing clinician, the successful candidate must hold, or be eligible for licensure with the College of Physicians and Surgeons of Ontario. Work
-
including metabolic rate assessment. Proficiency in quantitative image analysis of immunohistochemistry (IHC) and RNAscope datasets, including image segmentation, cell detection, signal quantification, and
-
ABIF can be found at: http://www.mcgill.ca/abif. Primary Responsibilities 1. Technical Development & Innovation Lead and document quality control (QC) workflows for ABIF imaging systems, including
-
for diagnosis and treatment, radiograph analysis, and patient outcomes in musculoskeletal care. The candidate will also work towards the development of ML projects to deal with multi-model datasets (text, images