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annum Apply by: 18/05/2026 Role Description We welcome applications from passionate and skilled researchers to join our team in the Centre for Digital and Design Engineering, contributing to the EPSRC
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 4 days ago
, experimental design, image analytics, machine learning, transcriptomics, or molecular phenotyping. Experience in the biological or agricultural sciences. For more information about the position please contact Dr
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Responsibilities: Develop chemical and biochemical assays and analyses, conduct comprehensive laboratory experiments, data analysis and reporting. Design, develop, and test microfluidic devices for miniaturised
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evidence of potential to deliver innovative, effective and enjoyable teaching Ability to design the basics of a future externally funded research project Some experience of effective and diligent academic
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mechanisms. Develop and optimize stimuli-responsive fibers and fabric systems for tunable and personalized thermal management. Design and perform experiments, analyze data, and prepare technical reports
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 4 days ago
undertake at ANU. The candidate should have working rights and be available to start by August 2026. Desirable Requirements: Experience in mixed models, experimental design, image analytics, machine learning
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demonstrate proof of concept. You will lead the technical activities related to modelling and experimental testing, including the design of test programmes and interpretation of results. The role will also
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annum We welcome applications from passionate and skilled researchers to join our team in the Centre for Digital and Design Engineering, contributing to the EPSRC-funded TransiT project, focused
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and test biological hypotheses to advance your research project. Plan, perform, record and interpret experiments informed by the current state-of-the-art. Collaborate with a multidisciplinary research
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with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures, and evaluate their ability to generalise across different process