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Overview: Full-time, Fixed Term for 3 Years Salary Academic Level A6-B1 ($102,047 -$115,303 p.a.), depending on post-PhD experience 17% Superannuation and Flexible Working Arrangements Based
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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
for robotics. This project is a collaboration with the Australian Defence Science and Technology. It aims to develop computational representations and methods for efficient sequential decision-making under
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Public Policy, providing cutting-edge research in areas such as econometrics, macroeconomics, data analysis, and quantitative methods. Our ideal candidate is comfortable in working independently with a
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experiments and take an active role in advancing the statistical methods employed at the Plant Accelerator® . The appointed individual will support plant scientists using our services to address a diverse range
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or nearly completed PhD graduate with experience in protein biochemistry to join the Herbicide and Antimicrobial Innovation Laboratory led by ARC Future Fellow Dr Tatiana Soares da Costa. Working
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Australian National University | Canberra, Australian Capital Territory | Australia | about 24 hours ago
bring: PhD in bioinformatics, computational biology or a related field. Experience or interest in applying computational methods to RNA/mRNA therapeutics. A demonstrated ability to publish high-quality
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Australian National University | Canberra, Australian Capital Territory | Australia | about 24 hours ago
events. The Person The successful candidate will hold a PhD in design or a related field, with an active research and publication agenda. The successful candidate will have experience in one or more of: co
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to generate data which can be coupled with robust and physics-informed machine learning and reduced-order modelling methods for model predictive control and reinforcement learning. PhD (or soon to be completed
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software (Prism, Origin Pro, Matlab etc) A good understanding of appropriate statistical analysis techniques Qualifications Mandatory: PhD or equivalent in relevant field. Please Note: Appointment to