28 postdoc-computer-science-logic Fellowship positions at Monash University in Australia
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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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. 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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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
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the Addiction & Impulsivity Research Lab and the Computational & Systems Neuroscience Lab . You will be part of a collaborative environment that integrates expertise in psychology, neuroscience and computational
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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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GPER agonists to prevent cognitive impairment in post-menopausal women. Working within the GPCR EcoPharmacology Laboratory at Monash Institute of Pharmaceutical Sciences (MIPS) and collaborating closely
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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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opportunity for an early-career researcher to contribute to cutting-edge, interdisciplinary research with real-world impact in environmental sustainability and materials science. As a Research Fellow, you will
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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