26 parallel-computing-numerical-methods-"DTU" PhD positions 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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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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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
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Research, Applied Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and Information Technology will also be considered, but it will further be required that they also have a
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid