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Field
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at the Melbourne Centre for Nanofabrication (MCN). This role offers a unique opportunity to work on pioneering platforms that are transforming how we model human physiology and accelerate therapeutic discovery. In
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of Engineering and contribute to industry-engaged research in construction materials and modelling. This role offers a rare opportunity to work across laboratory experimentation, scaled-up prototype testing, and
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Completion or near completion of a PhD in the discipline area (molecular biology, immunology, cancer research, pharmaceuticals). Experience in animal models of disease. Evidence of publications in reputed
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data with good utility. This project involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation
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mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems, diverse molecular techniques, and advanced imaging. The project will involve both internal and
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practice and policy · drive translational research activities such as evidence synthesis, economic evaluations, and implementation science approaches that support improved models of care for high‑risk
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of the project “PROSPER: Predictive models for sustainable protein recovery”, funded by FEDER and by National Funds through FCT (Operation No. 15391 — COMPETE2030-FEDER-00907300), under the following conditions
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, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three different research themes: (1) Planets and Early
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of persistent virus. 3. Single cell analysis of in vivo viral reservoirs and in vitro models of latency. 4. The innate immune response to HIV and mechanisms of immune evasion. The successful candidate will join a
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Research Fellow - Transport Modelling Job No.: 688348 Location: 533 St Kilda Road, Melbourne Employment Type: Full-time (negotiable) Duration: 12 month fixed-term appointment Remuneration:$118,974