307 phd-studenship-in-computer-vision-and-machine-learning Fellowship research jobs in Australia
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‘researcher’s journey’ program that exposes our Fellows to world leading researchers, mentoring, connections with Australia’s learned academies and more. Partner Universities The Fellowships can be held at any
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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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record of computer programming. Experience in numerical relativity and/or numerical simulation of quantum field-detector interaction Strong written and oral communication skills. Demonstrated ability
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 4 days ago
publications and fostering national collaborations. They may assist in course delivery, prepare online learning materials, mark assessments, and supervise student projects. The role includes mentoring students
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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) GRADE 7, £39,355 - £45,413 pa Fixed-term Ref: 095593 A Research Fellow position is available in the group of Professor M. J. Rosseinsky OBE FRS to work in a team of computer scientists and materials
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of leaders and innovators with the skill, commitment, and vision to protect vulnerable communities and truly advance health outcomes. It is at the heart of everything we do. About the Role Flinders
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modelling and machine learning to join and lead a dynamic international team of early-career researchers. This exciting role is part of a cutting-edge project investigating the structural integrity
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to demonstrate: A Completion of a PhD in a health-related discipline. Experience in qualitative and/or quantitative research methodology. The ability to plan and execute data collection and analysis. Experience
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in advanced signal processing techniques and good understanding of emerging machine learning methodologies used in NDE. You will work in close collaboration with project partners at the University