10 computer-programmer-"https:"-"IDAEA-CSIC"-"https:"-"https:"-"Dr"-"UCL" Fellowship positions at Monash University
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Research Fellow - Environmental Informatics Hub Job No.: 680160 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment (with the possibility of an additional 2
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Research Fellow in Computational Neuroscience Job No.: 686523 Location: Clayton campus Employment Type: Part-time, fraction (0.7) Duration: Fixed-term appointment until 30 November 2026 Remuneration
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program that advances the understanding within the scientific fields of brain and mental health. This position will contribute to the research priorities of the Turner Institute for Brain and Mental Health
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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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The Monash Suzhou Science and Technology Research Institute (MSSTRI) and currently has five priority research themes that address strategic issues of mutual interest, including: Advanced computation in science
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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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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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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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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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. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film