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Description: STA220H1F L0101 – The Practice of Statistics I (0.5 FCE) An introductory course in statistical concepts and methods, emphasizing exploratory data analysis for univariate and bivariate data
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methods described in statistical literature. Implements methods described in the statistical literature into operational computer applications using appropriate programming languages. Participates in
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methods dealing with model complexity - e.g., AIC, BIC, MDL, MML - can enhance deep learning. References: D. L. Dowe (2008a), "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008
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proposals to develop, optimize and deploy a headspace collection method to measure partition coefficients at physiological temperatures. We are especially interested in methods that target molecules
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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark
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Hyundai-NTU-A*STAR Corp Lab has a robotic pick and place project. We are seeking to hire a research associate to carry the computer vision part of the project. Responsibilities: Develop effective
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external fundings when appropriate. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team
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program in Physical or Mathematical Sciences. Topics include: electricity, magnetism, light, optics, special relativity. Number of Positions: 1 Estimated course enrolment: 196 students Estimated TA support
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of Positions: 1 Estimated course enrolment: 196 students Estimated TA support: TBA hours (contingent upon enrolment) Class schedule: Practicals: Monday and Wednesday 3:00pm-5:00pm and 5:00pm-7:00pm Lectures
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mathematical analysis, numerical exercises using Python, and participatory demonstrations of mechanical systems. Number of Positions: 1 Estimated course enrolment: 92 students Estimated TA support: TBA hours