56 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at The University of Queensland in Australia
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for the manufacture of computer chips. The project is supported by the Australian Research Council Linkage Project “Innovative Double Patterning Strategies for Integrated Circuit Manufacture” and is within
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providers and communities, informed by data from other ARC-IFC themes, and guided by relational Indigenous methodologies. Key responsibilities will include: Research: Establish a research program, collaborate
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an opportunity to develop a strong research profile and gain national recognition in the field. Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek and
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technologies that support decarbonisation and clean energy goals. The successful applicant will contribute to the computational modelling and design of Prussian blue analogues, spin-crossover metal-organic
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dynamic research environment. Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek and manage research funding, publish in reputable journals
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and emerging research profile in biotechnology and biopolymers. You will work with Professor Steven Pratt and other CI’s on delivering against the research objectives of Research Program 1.3
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opportunity to make a significant impact on both fundamental science and emerging applications Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek
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, including commercialisation of UQ intellectual property; develop a coherent research program and an emerging research profile; review and draw upon best practice research methodologies. Supervision and
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Fellow to join The University of Queensland’s Node of the EarthBank Program — a newly established national geoscience initiative under NCRIS AuScope. EarthBank is a transformative program aimed at
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You For Level A Applicants will have completed or be near completion of a PhD in quantitative genetics, animal breeding, computational biology, or a related field. Additionally, you will demonstrate