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that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3
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. Responsibilities and qualifications The nature of this project suggests that you should have a strong interest in the mathematical and theoretical aspects of machine learning. A solid background in mathematics (e.g
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13 PhD positions in Cohomology, Geometry, Explicit Number Theory (COGENT – Doctoral Network) Marie Curie Doctoral Network Funding Available Students Worldwide View DetailsApply Online
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Degree Doctor of natural sciences (Dr rer nat) Doctoral degree or degree awarded by University of Bonn Course location Bonn In cooperation with Bonn International Graduate School of Mathematics
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journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science/biomedical engineering or of relevant scientific field A solid background
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Are you passionate about mathematics and looking to embark on a journey of discovery? The Division of Algebra and Geometry is seeking a highly motivated PhD student to join our team. We seek a PhD
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open to Australian citizens who can meet the requirements for PhD admission at the University of Adelaide, and who can demonstrate suitable experience in Mathematics, Physics and/or Computer Science
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above, focusing on generative and Bayesian models relying on methods ranging from mathematics, algorithmic design, to implementation, and experimentation. Analyzing large-scale environmental datasets
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structures are nonlinear. This presents a major problem as the mathematics that we usually rely on have almost always been created with linear systems in mind. The way around this issue in the past has been
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analyses, mathematical modelling, or data analysis. But whatever the research approach, the goal would be to influence UK policy that increases protection of the UK population from current or future emerging