25 parallel-computing-numerical-methods-"Prof" PhD scholarships at University of Adelaide in Australia
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equations, and numerical methods. Advanced programming skills in languages such as Python, C++, MATLAB, or R. Strong academic curiosity and enthusiasm for the chosen research area. Application Process To
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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among higher degree by research students, and to promote knowledge transfer between academia
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research papers. Program overview The successful candidate will receive: Admission to a PhD program at the University of Adelaide; A University of Adelaide Research Scholarship for 3.75 years, paid
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learning. This program allows students to conduct cutting-edge AI research at a world-class institute and provides travel funding to gain valuable experience working with international collaborators in
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of Adelaide. Candidates should have experience with numerical methods and programming in Python/Matlab and be prepared to work with research volunteers. Eligibility: We welcome applications domestic applicants
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injection into a reservoir saturated by water from core scale up to the numerical cell or a reservoir is a challenge. For immiscible two-phase flow in layer-cake reservoirs, the models for pseudo relative
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quantitative data, as well as literature reviewing and policy analysis. Experience in these methods is desirable. A solid understanding of research methods, and an enthusiasm for building these skills, as
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herbicide and antimicrobial resistance that threatens the global agricultural and health industries. This exciting project will draw on parallels with drug resistance to investigate a new molecular mechanism
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upcycling of spent metal oxide cathodes, particularly, high Ni-containing oxides, through chemical-mechanical approaches, ionothermal/molten salt methods, etc. Project 2 (2 PhD students): Direct Recycling
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Chain Management. Candidates with a bachelor's and master's degree in Operations Research, Applied Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and Information