57 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at The University of Queensland
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coherent research program and apply best-practice methodologies. Supervision and Researcher Development: Support and supervise Honours and Higher Degree by Research students, foster researcher development
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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
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Develop a coherent research program and an emerging research profile in mathematical ecology or mathematical epidemiology. Participate in applications for competitive research funding to support projects
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert
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be involved in the supervision of UQ’s physiotherapy honours, masters and PhD students undertaking research at the Royal Brisbane and Women’s Hospital. In addition, you will support research, quality
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develop a research program in experimental Rotating Optical Tweezers for studies of complex biological systems. Innovate and pursue the aims of the Discovery Project on this subject, including conducting
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) Based at our Herston Campus . About This Opportunity Join a nationally significant program driving innovation in clinical trial methodology at one of Australia’s leading research institutions
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. The fellowship focuses on producing a suite of evidence to underpin innovation in the not-for-profit sector. Key responsibilities will include: Research: Establish a research program, collaborate on research
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You Completion or near completion of a PhD in psychology, epidemiology or public health Demonstrated experience analysing longitudinal quantitative data. Some experience with analysing qualitative data