612 embedded-system-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Monash University
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Institute (BDI) is one of the largest and most dynamic biomedical research and teaching environments in Australia. The Institute and its cognate Departments of Anatomy and Developmental Biology, Biochemistry
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Join a dynamic team at the forefront of healthcare innovation as a Research Fellow in the School of Nursing and Midwifery. Monash Nursing and Midwifery is seeking a dedicated and motivated Research
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-screen). Experience with these and associated techniques is highly desirable. Experience in the organic synthesis of small molecules is also desirable but not essential. The candidate will also contribute
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-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
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position, you will bring your specialist expertise in land use, ecosystem services, biodiversity, agriculture or food systems to guide, deliver and elevate high-impact research that informs national decision
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responsible for coordinating participant registrations, managing session logistics, supporting stakeholder communications and maintaining accurate program data, while building strong working relationships with
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of Information Technology is seeking a proactive and highly organised Department Officer to provide essential administrative support across its Departments. This is a key role which supports delivery of a range of core
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The Opportunity Monash University is seeking an accomplished executive leader to drive the strategy and operations that power our fundraising and alumni engagement success. Reporting to the Vice-President
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. The goal is to find common brain mechanisms and networks that are effected by different kinds anaesthetics to see if this points to a 'backbone' for the generation of consciousness. Required knowledge
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hospital or population often fail when applied elsewhere due to distributional shifts. Since acquiring new labeled data is often costly or infeasible due to rare diseases, limited expert availability, and