28 computer-aided-manufacturing Fellowship positions at Monash University in Australia
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Research Fellow - Environmental Informatics Hub Job No.: 675993 Location: Clayton campus Employment Type: Full-time Duration: 3-year fixed-term appointment Remuneration: $83,280 - $113,025 pa Level
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Research Fellow, Systems and Computational Neuroscience Job No.: 676758 Location: Clayton campus Employment Type: Full-time Duration: 2-year fixed-term appointment Remuneration: $80,464 - $109,203
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Research Fellow - Quantum Control and Quantum Computing Job No.: 667644 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment Remuneration: $114,951 - $136,505
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the Faculty, the Department of Electrical and Computer Systems Engineering (ECSE) offers internationally acclaimed programs in power systems, telecommunications, electronics, robotics and biomedical engineering
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industry, policy, and public sectors Review relevant literature and engage with sociological theory to understand the role of “cute” home helper robots in Australian households Undertake design and digital
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Computer Science, Computational Chemistry, bioinformatics) and have extensive experience in academia or industry with a focus in computational drug discovery. Prior experience working with GPCRs would be
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background in clinical research and a genuine interest in chronic lung disease and supportive care. In this role, you'll work closely with the Group Lead, coordinating research efforts, supervising students
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programs, ensuring a rigorous foundation in quantitative disciplines while maintaining strong industry and research partnerships. About The Research Fellow Opportunity This is an exciting opportunity for a
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-centred care. Highly organised and detail-oriented, with strong time management skills and a proven ability to manage competing priorities, maintain rigorous documentation, and ensure adherence to clinical
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are seeking a Research Fellow to contribute to a project funded by the Australia Economic Accelerator (AEA) Ignite program, focusing on the design and integration of a novel point-of-care diagnostic platform