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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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duties. Ability to effectively manage time and see assigned parts of projects through to completion on deadline. Proven ability to juggle multiple related projects in parallel with concurrent and staggered
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or life sciences, computer science or related field; PhD preferred Two (2) years to three years of experience in developing parallel computing applications, libraries or software tools working with
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independently a wide variety of technical procedures in a section of the Clinical Genomics Department. Other responsibilities include method development-modification-parallel testing, collaboration
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times through higher parallelization and enable targeted stimulation of hardware faults by adjusting the models. To this end, a simulation environment based on a virtual prototype will be developed using
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project management skills, and the ability to prioritise work, work to deadlines and undertake multiple parallel projects Demonstrated ability to identify, assess, test and evaluate technical applications
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of custom computer code, and the processing of large-scale simulations using massively parallel resources such as NERSC and Raj cluster at Marquette. Conduct research with a significant degree of independence
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opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel
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include high-performance computing, middleware and computing systems. Recent relevant research experience to include: Undertaking research in the area of high-performance / distributed / parallel computing