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students; and 54 MS students) degrees. The McGowan Institute for Regenerative Medicine (https://mirm-pitt.net/ ), Computational and Systems Biology (https://www.csb.pitt.edu/ ), the Vascular Medicine
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
and teaching, the professorship will represent functional cardiovascular imaging with a focus on hemodynamic modeling and act as a bridge between basic research, medical technology development, and
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Intelligence Learning department of the Computing and Data Sciences (CDS) directorate at Brookhaven National Laboratory (BNL) invites exceptional candidates to apply for a post-doctoral research associate
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. In particular, he/she will be expected to :• Select and evaluate the most suitable approaches from the wide range of machine learning and computer vision methods available in the literature, with
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Imaging Hospital Affiliation: University Health Network (UHN) & Sinai Health System (SHS) Campus: St. George (Downtown Toronto) Existing Vacancy: Yes Description: The Joint Department of Medical Imaging
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experience with imaging, image processing, and/or visualization, as well as excellent programming skills. You must have a relevant Master's degree in computer science, electrical engineering, imaging science
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, industrial and international partners. SnT is active in several national projects funded by National Research Fund (FNR) and local industries, and international research projects funded by the EU FP7 program
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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diagnostic imaging, and provides perdiem radiologic and ECG services as needed. The position requires strong technical skills, attention to regulatory standards, and effective communication with campus
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workstation for extended periods of time and performing tasks with repetitive motions (such as typing). Also involves some risk of injury from moving, lifting or positioning patients, equipment, or materials