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Field
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/materials science, AI/ML, and computational modelling (DFT, MD, etc.) Good publication record Good written and verbal communication skills Proficiency in programming We regret that only shortlisted candidates
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development of next-generation computational tools for simulating particle-laden two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics
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features in alloys, to aid future alloy design. The UNSW team, lead by A/Prof Patrick Burr, will provide the modelling contributions, and the team at USyd, led by Prof Julie Carney and Dr Ranming Liu, is in
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apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics datasets spanning a range of model
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computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
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computational modelling and multi-level modelling analyses; working closely with the head of the lab and the other team members, and inputting on supervision and line management of current and future research
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Assistant (two posts) [Appointment period: each for twenty-four months] Duties The appointees will assist the project leader in the research project - “Metal forming technologies and numerical modelling
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Launch your career at Australia’s leading scientific research organisation! Exciting opportunity for an early career researcher with a PhD in Mathematics, Data Science, or Computer Science Join the
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computational biology, who works well within a team. Excited about developing and applying cutting-edge ML/AI models to solve open problems in genomics and biology. Preferred Qualifications: Experience with
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students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental/School research