17 postdoc-computational-fluid-dynamics-2017 Fellowship research jobs at Australian National University
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Classification: Academic Level B Salary package: $118,632 - $134,507 per annum plus 17% superannuation Terms: Full time, Fixed term (up to 3 years) The Position This postdoc will explore
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, attention-based models, and multi-modal learning approaches—to model RNA-mediated regulatory mechanisms and their dynamic interactions in disease. The position is part of an NHMRC Ideas Grant project
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distinctive community of multi-disciplinary and area specialists dedicated to research, education and engagement in the world’s most dynamic region. CAP is the global centre of excellence for understanding
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
independent research in molecular biology and biophysics, focusing on computational simulations to examine protein structure and function. This includes using advanced sampling methods and free
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presentations. The successful candidate will have the opportunity to contribute to a collaborative and dynamic research environment, with access to state-of-the-art facilities and resources. This position offers
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design, data analysis, and dissemination of findings through publications and presentations. The successful candidate will have the opportunity to contribute to a collaborative and dynamic research
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. This position is suited to experienced researchers ready to influence the direction of nuclear physics research within a dynamic and collegial academic setting. Ideal Candidate Academic Level A – Postdoctoral
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platform with global ambitions. The Position Funded through the Medical Research Future Fund (MRFF), this position will play a central role in developing computational tools and AI-based approaches
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University. Located within the School of Art and Design, the Design program combines contemporary design methods and digital technologies with hands-on making. It prepares graduates who are skilled, inventive
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to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human-centered ML, or NLP. Supported by an ARC Future Fellowship and CSIRO-NSF project. Computational