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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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models Applying imaging modalities to support drug distribution and efficacy studies Collaborating with national partners across a multidisciplinary research network This position offers a unique
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multi-organ-on-a-chip platform. Leveraging advanced microfluidics, live-cell imaging, and integrated biosensing technologies, you will help generate multi-parametric insights into barrier integrity
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Demonstrated awareness of confidentiality and responsible data handling Experience in cell signalling, cellular imaging or mouse models of cancer will be highly regarded. About the Institute and Department
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brain state, maintain barrier integrity, and contribute to neurological disease, including brain cancer and stroke. The lab integrates advanced imaging, omics approaches, mouse genetics and flow cytometry
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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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“Revealing Order in Organic Semiconductors with Cryo-Electron Microscopy.” The successful candidate will apply and develop advanced cryo-electron diffraction and imaging methods to uncover structure–property
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methods, and, more broadly, in the physics of imaging and materials science. The position will work in close collaboration with Professor Jian-Min Zuo, Director of the Monash Centre for Electron Microscopy
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, and, more broadly, in the physics of imaging and materials science. The position will utilise instruments in the Monash Centre for Electron Microscopy which has a powerful suite of instrumentation