317 postdoc-in-thermal-network-of-the-physical-building Fellowship positions in Australia
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research settings. You will be expected to lead high-quality research projects, publish in top-tier journals, attract competitive research funding, and build collaborative networks both nationally and
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thrives in interdisciplinary and applied research settings. You will be expected to lead high-quality research projects, publish in top-tier journals, attract competitive research funding, and build
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 17 hours ago
community at ANU. The successful candidates will join teams working on projects that span core AI research and interdisciplinary collaborations through the ANU Integrated AI Network (ai.anu.edu.au), focusing
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the Zero Net Emissions Agriculture CRC initiative , focusing on developing tropical grasses with low methanogenic properties to help combat agricultures impact on our environment. This position contributes
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research focus areas. The Research Fellow will embed their research expertise into the life of the School through the development of high-quality, productivity driven research networks across RMIT and with
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proteins, combined with methods such as microscale thermophoresis will also be used to characterise enzyme activity. The postdoc will also co-supervise PhD students and Honours students. Outputs will include
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from the recruitment process, not to make an appointment, or to appoint by invitation, at any time. We reserve the right to remove the advert earlier than the date on the advert.
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PRIMARY DETAIL • Build your academic networks and career, access cutting-edge facilities and technology • Salary package: $109,897to $113,697 p.a. (Level A Step 7- 8), plus 17% employer’s
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. Demonstrated ability to supervise higher degree by research candidates. Ability to build effective networks with colleagues and generate alternative funding projects through effective liaison with industry and
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experienced Postdoctoral Research Fellow B to undertake research in the field of physics-informed neural networks for magnetic sensing. This project combines the strengths of industry and academia to leverage