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Research Associate in Metallomics and Chemical Biology with the primary responsibility of performing metallomics studies including the preparation of responsive fluorescent sensors for application in
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(AIED) and Educational Data Mining (EDM) projects with Professor Kalina Yacef. These projects explore how multimodal data from online platforms and sensor-based environments can be harnessed to enhance
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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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international collaboration involving a wide network of Australian and international researchers investigating fossil reef systems from across the Indo-Pacific, including the recently drilled International Ocean
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to the supervision of undergraduate and postgraduate students. The ARC-funded project is an international collaboration involving a wide network of Australian and international researchers investigating fossil reef
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network of academic, industry and professional partners and stakeholders skills in qualitative research methods and ability to lead research involving interviews and focus groups experience conducting
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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging
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populations. Additionally, this role will be coordinating with a network of researchers across seven countries: the UK, Austria, Canada, Singapore, China, Germany, and Australia to organise and implement
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Rheumatology have a network of relationships with key academic and professional institutions, partners and stakeholders that can be leveraged to enhance the standing of the Specialty, Hospital/School/Faculty and
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activities. The Sydney EarthBank node will join the national AuScope Geochemistry Network , an Australian consortium of Earth Science institutes cooperating to develop national geochemistry research