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Acknowledgment of Country Australia's Chief Scientist and the Office of the Chief Scientist recognise the first peoples of this nation and their ongoing cultural and spiritual connections to the lands, waters, seas, skies, and communities. We acknowledge First Nations peoples as the Traditional...
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intelligence as a Professorial Research Fellow in AIML. To be successful you will need: A doctorate (or equivalent) and research experience in computer science, machine learning, AI/software engineering or a
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enrolment in a graduate program in Economics at an overseas university or research institution. (Note: An academic reference is a letter from an academic at your university who is familiar with your research
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area, such as ecology, computational biology or bioinformatics. Please note: To be eligible for this role you must have no more than 3 years (full-time equivalent) of relevant postdoctoral research
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for a National Intelligence Discovery Grant (NIDG) project, in collaboration with researchers in the School of Computer Science and Electrical Engineering who are focusing on antenna design. It is
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PhD in Forensic Science, Electrical Engineering, Computer Science, Data Science, Criminology or related area (or near completion). A record of high-quality research outputs, including publications
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using computational approaches, present results at conferences and scientific meetings, prepare manuscripts for publication, and collaborate with colleagues on joint research projects, develop a research
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, epidemiology, biostatistics, health services research, implementation science, behavioural science, qualitative research or health policy. Applicants may have experience in these research fields, either at a
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. You will work closely with Professor Ali Abbas (School of Chemical and Biomolecular Engineering ) and Professor Gregor Verbic (School of Electrical and Computer Engineering ), in partnership with
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to this project. The ideal candidate will have: Strong skills in data science, user experience design, and/or web development, with the ability to apply human-centred computing/engineering methods to digital health