13 distributed-algorithm-"Prof" Fellowship positions at The University of Queensland in Australia
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. Strong time-management skills and ability to meet deadlines. Ability to work collaboratively in cross-disciplinary, geographically distributed teams. Desirable Knowledge and experience in sorghum or other
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change, and we’ll help you get the best start to your academic career at one of Australia’s leading universities. Supported by several ARC research grants awarded to A/Prof Sarit Kaserzon, this is an
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and Dr. Daniel Stjepanovic on a range of NHMRC-funded research projects (e.g., social media and addiction, AI-assisted intervention), and work under the supervision of the Prof. Jason Connor, Director
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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learning and mechanistic modelling, sensor network development, efficient data sorting and processing algorithms, real-time and model predictive control, and transformative applications in the wastewater
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at UQ . Questions? Contact A/Prof Patrick Harris at p.harris@uq.edu.au for role-specific queries. For application support, email recruitment@uq.edu.au and quote job reference R-55549. Want to Apply
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are not available for this appointment. Questions? For more information about this opportunity, please contact Prof Keith Chappell - k.chappell@uq.edu.au For application inquiries, please reach out
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via the academic promotions process. Questions? For more information about these opportunities, please contact A/Prof Sarah Wallace at s.wallace3@uq.edu.au . For application inquiries, and to request
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. Questions? For more information about this opportunity, please contact Prof Michael Yu - c.yu@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au
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-based hail climatology for France, Switzerland and Northern Italy, including hail swaths per event across more than a decade. Design, develop and train geostationary satellite-based hail algorithms using