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Research Fellow, Implementation Science in Addition Treatment Job No.: 683764 Location: Turning Point, 110 Church Street, Richmond Employment Type: Full-time Duration: 12-month fixed-term
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communities globally by promoting and supporting the use of the best available evidence to inform decisions made at the point of care. This work begins and ends with the needs of those working in and using
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measuring prediction error signals in the brain. You will support the compelling hypothesis: a key function of sleep is to balance prediction and surprise. Key responsibilities will include: Research: Produce
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charge which provide an ideal interface between human-built devices (where signals are carried by electrons) and biological systems (where signals are carried by ions). This research will cover theoretical
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or doctoral qualification in neuroscience or a closely related field, and a strong background in signal processing, programming and electrophysiological techniques. Demonstrated skills in data analysis and
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translational clinical research. The successful candidate will be responsible for the design, development, and characterisation of a diagnostic electrochemical biosensor, incorporating signal processing and
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in advanced signal processing techniques and good understanding of emerging machine learning methodologies used in NDE. You will work in close collaboration with project partners at the University
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, please refer to 'How to apply for Monash Jobs '. Your application must address the Key Selection Criteria. Please indicate whether you are applying at Level A or B, depending on your experience and
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of the projects, acting as the first point of contact for all enquiries related to the research projects, research proposal, and provide support for the school's research operation management, including developing
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis