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management (Matlab, MySQL) •May be trained to process neuroimaging data on the UMN MSI and CMRR servers: HCP and inhouse pipelines (e.g., ANACONDA, Python, FSL, AFNI, SPM, CONN) Managerial tasks, oversight and
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organizational skills o Time management Preferred Qualifications: • Experience with rodent handling • Programming experience (R, Python, or other data science languages) • At least a two-year commitment to the lab
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 5 hours ago
: About us: U of T Mississauga—the second largest campus of Canada’s top-ranked university and the only research university in Ontario’s booming Peel Region—is one of the world’s great catalysts of human
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of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is
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of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare
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, Python, or statistical software (SPSS, Excel, etc.) Conduct literature reviews and contribute to drafting research publications and reports Maintain detailed records of procedures, results, and equipment
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operations management, proficient in Python, and the ability to manage grades and course admin tasks on Quercus. Class Schedule: Courses may be online or in person depending on circumstances, so candidates
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incorporating hardware and research devices. Primarily requires the use of Python and associated libraries (Numpy, PyQT/PySide6, Pandas), but may also involve the use of MATLAB/Simulink and C++. At direction
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essential, along with scripting skills in R and Python for bioinformatics data processing, visualization, and reproducible workflow development. Strong organizational skills are essential, along with
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technical knowledge and hands-on experience in: Deep learning frameworks (e.g., PyTorch, TensorFlow) Deep learning models (e.g., YOLO, U-Net, EfficientNet, ResNet, FPN, Fast R-CNN) Computer vision techniques