372 professor-computer-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"St" positions at Monash University
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Duration: 3.5 years fixed-term appointment Supervisory Team: Professor Elizabeth Manias (Main Supervisor) The successful candidate will be supported by a multidisciplinary project team with expertise in
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. This work combines computational modelling and simulation with biological experiments that are analysed using cutting-edge computer vision techniques. We collaborate closely with Macquarie University where
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-employment and/or background checks required for the role, as determined by the University. Enquiries: Associate Professor Daniel Horsley, School of Mathematics, daniel.horsley@monash.edu Position Description
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
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Ashton Nixon Scholarship Sir John Monash Scholarship for Achievement The Ashton Nixon Scholarship is supported by Associate Professor Rosemary Nixon AM to support undergraduate students embarking
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classification'', Computer Journal, Vol 11, No 2, August 1968, pp 185-194 Wallace, C.S. and D.L. Dowe (1999a). Minimum Message Length and Kolmogorov Complexity, Computer Journal (special issue on Kolmogorov
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Monash Leaders Scholarships Monash Leaders Scholarships are awarded to applicants that demonstrate leadership and commitment to give back to the community through the Access Monash Mentoring program
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Goal Recognition is the task of inferring the goal of an agent from their action logs. Goal Recognition assumes these logs are collected by an independent process that is not controlled by the observer. Active Goal Recognition extends Goal Recognition by also assigning the data collection task...
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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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