10 bayesian-object-tracking Fellowship positions at University of Adelaide in Australia
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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Criteria: A PhD in applied mathematics, engineering, computer science, data science, physics, or a related area. Strong academic track record (including peer-reviewed publications and conference
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, monitoring workflow and in managing resources to meet objectives, timelines and deadlines. Excellent oral and written English language skills and a demonstrated ability to communicate and interact effectively
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science or environmental data sharing. Track record of contributing to competitive research funding applications or demonstrated potential to support grant writing. Experience in mentoring or supervising
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management decisions and mitigate risk. The successful candidate will develop the research objectives in collaboration with an experienced supervisory panel, comprised of researchers at the University
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. Expertise and interest in stem cell biology, epigenetics and associated techniques. Outstanding academic track record (including peer-reviewed publications and conference presentations) and demonstrated
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entomology or a related discipline. A track record in entomology research or related field, evidenced by papers in peer-reviewed journals or equivalent. Demonstrated ability to work and communicate with
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discipline relevant to the core business of the RAIR Centre. A leadership style that fosters collaboration, inclusion, respect and team development, with a track record of leading diverse, high-performing
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projects, preferably in primary care or related fields Demonstrated experience leading quantitative data analyses and the reporting of health research findings Track record of health-related publications
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, engineers and students. The group works on a variety of fundamental and commercially oriented research projects in computer vision and machine learning and has a very strong track record of publications in