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Field
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collaboration with diverse research and industry partners. You will optimise selection and mating strategies to accelerate multi-trait genetic gain, and contribute to the development of elite hybrid combinations
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research, combining innovative theoretical and methodological approaches to address how health services and systems can better meet population needs. Now, we are looking to accelerate our success after
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of concrete samples by alternating short-term model predictions and accelerated aging experiments on reconstructed aged-equivalent samples. The methods to develop and adopt will be: for O1, literature review
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for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components
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School of Medicine. The centre aims to improve population health and well-being and healthcare delivery by accelerating evidence-based practice through the use of behavioural and implementation science
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with an industry partner and the UK Space Agency. Key responsibilities include: Developing a second-stage plasma accelerator based on magnetohydrodynamic (MHD) principles. Optimising ICP (Inductively
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collaborations between the Department of Biosciences, the Natural History Museum, the Department of Mathematics, and the Department of Philosophy. To respond effectively to the accelerating decline in biodiversity
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about Monash . Today, we have the momentum to create the future we need for generations to come. Accelerate your change here. Monash supports flexible and hybrid working arrangements. We have a range of
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this, we have recently launched the London Sustainable Materials Lab (LSML)—a cutting-edge facility designed to accelerate innovation, testing, and knowledge exchange in sustainable materials. About the Role
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to accelerate digital innovation and research capabilities within the Austin Hospital ICU. In this 0.5 FTE, Level B research-only role, you will play a key part in transforming clinical data into actionable