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approaches specifically tailored for these low-data applications that are reliable and robust against noise. You will support our team in developing reliable machine learning methods that can be applied
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major themes in the course. Estimated course enrolment: 25 students Estimated TA support: N/A Class schedule: Tuesday 10am-1pm (Lec. 0101) and/ or Thursday 1-4pm (Lec. 0102) *The delivery method
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for their final course assignment. Estimated course enrolment: 95 students Estimated TA support: TBA Class schedule: Lecture: Fridays 9.30am-12.30pm (in-person) *The delivery method for this course is expected
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. Estimated course enrolment: 25 students Estimated TA support: 35-hours Class schedule: Wednesdays 9-12 and/or 2-5pm *The delivery method for this course is expected to be in-person. Please note that, in
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achieving net-zero greenhouse gas emissions by 2050. Estimated course enrolment: 35-40 students Estimated TA support: 45-hours Class schedule: Wednesday, 10am - 12.30pm *The delivery method for this course is
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, improving and monitoring techniques, and developing innovative methods and approaches to solve scientific problems while meeting goals and objectives in accordance with priorities, time, funding, and other
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demonstrate a high degree of technical competence and knowledge in current methods and techniques. Qualified candidates will demonstrate superior patient care and possess outstanding communication skills
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on human health. Provides a foundation for advanced studies in bacterial physiology, bacterial genetics, molecular pathogenesis of disease, immunology, and environmental studies. Estimated TA support: 180 TA
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texts. By using a mixed method approach, we propose to make the erased texts readable again, and then edit, translate and study them. Combining multispectral image capture and analysis with machine
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knowledge of the methods, materials, and equipment used in custodial operations Demonstrated excellent communication skills Demonstrated computer skills including Microsoft Office (Excel and Word) and Google