65 parallel-computing-numerical-methods-"Simons-Foundation" research jobs at The University of Queensland in Australia
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coherent research program and apply best-practice methodologies. Supervision and Researcher Development: Support and supervise Honours and Higher Degree by Research students, foster researcher development
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team to drive innovation in plant breeding. Key responsibilities will include: Research: Conduct and publish high-quality research, develop a coherent research program, and actively pursue competitive
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Physics, Chemistry, Materials, Chemical Engineering, or a closely related discipline. Broad knowledge of kinetic Monte Carlo methods. Demonstrated expertise in one or more of the following areas: ab initio
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geomechanics, or ability to quickly acquire relevant domain knowledge. Proficiency in high-performance computing (HPC) for large-scale parallel simulations. Experience with advanced constitutive models and their
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imposed timelines/milestones. PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD. Proficiency with open-source engineering software and numerical methods such as FEM
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completion of a PhD in geomechanics, energy engineering, geophysics, and/or geodynamics. An established record of scientific achievements in geomechanics and geomechanical numerical modelling, including
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to deploy soft sensors in real-time environments. Key responsibilities will include: Under the guidance of senior researchers, program process models for the minerals processing industry Assist with
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independently and design/interpret experiments using in vivo animal models and ex vivo methods, adhering to PPE requirements (including PAPR use with restricted carcinogens). Demonstrated critical thinking
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their potential for antibiotic production. Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek and manage research funding, publish in reputable
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. The successful candidate will develop computational tools for analysing gene expression (single cell, spatial) and metabolomic data in the context of cancer including melanoma and pancreatic cancer. You will lead