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research profile as a Research-focused Academic in the Queensland Alliance for Agriculture and Food Innovation at UQ. The Research Fellow will be responsible for leading a tissue culture program for
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peer-reviewed literature An interest in global change ecology, macroecology, biogeography, or conservation biology Strong computational and analytical programming skills A good knowledge of advanced
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
for the design of therapeutic RNA candidates. The successful candidate will be based in the Centre for Computational Biomedical Sciences and will contribute to the delivery of the NTRP's mission to grow
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-object tracking, trajectory reconstruction, and error reduction. About you Tertiary degree in Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent
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opportunity to translate your computational results to practical design, engineering and structural and functional characterisation of the novel nanoparticles for applications in biomedicine. About You You will
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modeller to help lead a collaborative research programme between the University of Queensland and King Abdulla University of Science and Technology (KAUST) with Prof David Suggett. Our shared goal is to
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are looking for - Selection Criteria: Essential: A PhD in a relevant discipline such as Applied Statistics, Mathematics, Bioinformatics, and/or Computational Genetics, Data Science. A demonstrated track record
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of Mechanical and Mining Engineering, where innovation meets impact. As a key member of this dynamic team, you will develop cutting-edge computational models of two-phase flow in fractured media — ranging from
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), fixed-term position for 12 months (with possibility of extension subject to funding availability and performance) - Location: Faculty of Medicine, Health & Human Sciences at Macquarie University
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Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with an excellent academic record. Demonstrated expertise and leadership in computer vision and machine learning research