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interdisciplinary research on the determinants of human health, well-being and development. We support secure research access to individual-level, de-identified longitudinal data on 5.4 million residents living in
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application of these techniques to the domain of information science. Topics will include software principles and practices, programming concepts and techniques, data structures, and algorithms. This course is
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Postdoctoral Fellowship in Quantum Navigation Two postdoctoral positions are available immediately in Professor Cory’s laboratory for the development of a quantum navigational device in
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for outcome assessments for a range of brain diseases. The individual will schedule, train, and supervise research assistants, students, and instructors. They must ensure: 1) patient confidentiality and safety
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a training dataset for developing machine learning algorithms for increasing the consistency of quality control in two cohort studies: healthy controls and epilepsy patients. Key Responsibilities
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Number: COMP 251 - Course Title: Algorithms and Data Structures Hours of work (per term): 90 Required duties: • - effectively and timely communicate with the instructor and the students; • - maintain
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Number: COMP 360 - Course Title: Algorithm Design. Hours of work (per term): 90 Required duties: • - effectively and timely communicate with the instructor and the students; • - maintain and observe
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repositories programmed in Python, Pytorch, LangChain using git repo. Develop clean, readable, and maintainable public code using object-oriented programming principles in Java and Python. Apply machine learning
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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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, strings, pointer-based data structures and searching and sorting algorithms. The laboratories reinforce the lecture topics and develops essential programming skills. Estimated course enrolment: ~150