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nanotechnology-based approaches to modulate the immune system and create enhanced translational immunotherapy strategies in cancer. To be successful you will need: Completion of PhD (within last 5 years
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of infectious diseases. The role is part of MRFF Genomics Health Futures project aimed to apply microbial metagenomics to reduce infection risks among culturally and linguistically diverse communities in Sydney
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of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate who has: a PhD in mathematics, applied mathematics, computational mathematics or a closely related discipline a
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education, we are proud to be training the next generation of medical scientists who will be leading members of the medical research community with an innovative integrated curriculum. Our team of researchers
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interacts with students, staff and other members of the University community in a professional, collegial and respectful manner maintains an understanding of the University’s strategic agenda and contributes
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developing and patenting new IP, with great impact for the fusion and materials communities. The successful candidate will join A/Prof Patrick Burr’s diverse and multicultural research group. To learn more
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Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion
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conference presentations. provide informal mentoring and guidance to junior team members, including undergraduate and PhD students foster a positive and inclusive workplace culture that values diversity
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Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion) in FPGA design, machine learning or a
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and are looking for a Postdoctoral Research Associate AI-Driven Sensing and Control for Megaproject Systems who has: a PhD or near-completed PhD in one of the following fields (or closely related