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Research Fellow - Advanced Signal Processing and Machine Learning Techniques for Vital Signs Measurement from Video Images Job No.: 691722 Location: Clayton campus Employment Type: Full-time
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econometric skills and proficiency in statistical programming using software such as Stata, R, or Python. Experience with administrative data and knowledge of advanced techniques, including structural
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. Excellent written and verbal communication skills are essential, as is a collegiate approach to working with others. You will also have advanced computer skills, including experience with Microsoft Word
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will have: A PhD (or equivalent experience) in medicinal or synthetic chemistry Strong hands‑on laboratory experience in synthetic organic or medicinal chemistry Excellent analytical, organisational, and
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comparing model predictions of observed transient data Experience in software development with larger scientific codes; in particular, expertise in Fortran, C, Python, and/or build systems are of advantage As
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well as alongside two PhD students also funded to work on the project. The research will be supported by Monash’s world-class research infrastructure in electron microscopy. This includes the Monash Centre
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postgraduate qualification in Data Science / Computer Science (PhD preferred) Strong expertise in Python and/or R, SQL, data engineering and machine learning Experience with EMR systems (Cerner highly desirable
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activities. The successful candidate will have: A PhD qualification in medicinal or organic chemistry Experience in the synthesis of small molecules An understanding of pharmacology and/or drug development
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qualitative research and familiarity with analytical software (e.g., SPSS, Qualtrics,NVivo, RevMan) Experience working with participants with neurological conditions will be highly regarded. About Monash
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Science and Artificial Intelligence, with a focus on visual reasoning and robotic systems. The Research Fellow position involves developing novel approaches that integrate computer vision, natural