29 computer-science-programming-languages-"Prof"-"Prof" Fellowship positions at Monash University
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) using a beam blanker to solve important problems in materials science. The position will develop and apply methods using an aberration-corrected FEG-TEM with beam blanker and pixelated, single electron
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international peers working on the program, industry and government stakeholders, and funding bodies. Exploring, leading and coordinating opportunities for new research proposals, initiatives, or collaborations
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. We are currently seeking a Research Fellow with experience in AI and machine learning research and development, with a focus on any or all of following application areas: Computer vision Generative AI
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, languages and social sciences. The Postdoctoral Research Fellow in Indonesian History sits within the School of Philosophical, Historical and Indigenous Studies which undertakes teaching and research in
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problems in condensed matter physics and materials science. The successful candidate will exploit aberration-corrected FEG-TEMs with tailored electron-optics and pixelated, single electron detector systems
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Research Fellow in Fractional Edge Decompositions of Graphs Job No.: 687653 Location: Clayton campus Employment Type: Full-time Duration: 2-year fixed-term appointment Remuneration: $83,280 - $113,025 pa Level A (plus 17% employer superannuation) Amplify your impact at a world top 50...
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evaluate methods via experiments, benchmarking, simulation and/or real‑world data. The successful candidate will have: A PhD in Statistics, Data Science, Computer Science, Mathematics, or a related field
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#1 Chemical Engineering Department at Monash University and be part of a pioneering research initiative at the intersection of materials science, automation, and artificial intelligence. As a
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computational modelling, physics, mathematics and/or scientific programming backgrounds, ideally with experience in Earth System modelling, Earth science or related disciplines. Ideal technical requirements
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the guidance of artificial intelligence techniques. The project will develop novel design processes that embed material behaviour within agent-based and machine learning computational design systems