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addressing the skills and experience listed in the Position Description. A copy of the Position Description can be found on JOBS@UNSW . Contact For more information please contact Frank McHenry, Talent
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research on designing mobile energy hubs, energy systems integration, resilience analysis, and developing digital twin models and AI-enabled algorithms. You will conduct lab and field tests, analyse data
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of transitions in both domains. The successful candidate will be expected to develop testable hypotheses that can be applied to new model systems, such as bee colonies, in collaboration with the project team
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
candidate will be expected to develop testable hypotheses that can be applied to new model systems, such as bee colonies, in collaboration with the project team. The research will be conducted in close
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record of publications in top-tier venues such as SIGMOD, VLDB, ICML, NeurIPS, ICLR, or TPAMI. You may also: Have a strong background in machine learning, particularly foundation models for spatial data
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the people who discover them The Opportunity This Research Fellow position sits within a Wellcome-funded initiative focused on evaluating animal models in mental health science and developing a publicly
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the project titled “Fine Tuned Biometric Models for Warfighters in Austere Settings”, funded by the Office of Naval Research Global (ONRG). The Path to Adelaide University We are on an exciting path to Adelaide
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broad range of contemporary health-care related issues including: • Health Services Innovation • Integrated Care Models • Health Workforce Development • Symptom Management. What you need to succeed
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outcomes to end users. Coordinate the upload and curation of at least 250 samples annually to the EarthBank platform and contribute to data model development and refinement. Teaching: Support EarthBank’s
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, Software Engineering, or a related field. Demonstrated experience in deep learning and large language model research, joint modality representation learning, knowledge graph construction, particularly in