30 parallel-computing-numerical-methods-"Prof" research jobs at University of Adelaide
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is working to be the state’s world-class cancer research institute, jointly resourced by the Federal Department of Health, CALHN and the University of Adelaide. Reporting to Associate Prof. Robin Hobbs
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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computer vision and machine learning research group in Australia -- and contribute to world-leading research projects at the CommBank Centre for Foundational AI This postdoctoral research position is part of
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media; the development and application of numerical methods of image and signal analysis The ability to work well with people both in academia and Industry The ability to plan and manage own research
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applications in other multidisciplinary fields. The successful applicant will be required to undertake both experimental work and numerical studies. They will be expected to liaise with key institutes such as
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-performance computing (HPC), Bragg Crystallography facility, and Adelaide Proteomics Centre. Our collaboration with Monash University further extends our access to advanced 300 kV Titan Krios and Helios 5 UX
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this advertisement before the closing date if a suitable candidate is identified. For further information For a confidential discussion regarding this position, contact: Assoc. Prof. Bastien Llamas Group Leader
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demonstrated proficiency in qualitative and/or multivariate quantitative research methods and analysis, have experience in supporting the management of a large research program, and have demonstrated an ability
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responders and operational risk assessment regarding skin decontamination and will build on a program of work focused on dermal exposure to chemicals. To be successful you will need: Completion of a PhD in
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reduction reaction, N2 reduction reaction, and C-N coupling. Experience in applying machine learning methods to support materials computations. Demonstrated ability to collaborate effectively with researchers