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support staff and about 20 Postdocs and 30 PhD candidates. The Ice and Climate group at IMAU is an inspiring, high-quality and versatile research group focusing on ice sheets, sea level, and climate
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insight into the microscopic properties of the quark-gluon plasma. Other applications of energy correlators will also be investigated. You will be part of a research team, currently consisting of 2 postdocs
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Intelligence Centre external link , you'll join a large group of PhD candidates and Postdocs working on related topics. On a daily basis you will join the several PhD candidates and Postdocs that are based
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. These methods are applied and validated in practice and are often available as software packages. In addition, Biometris provides education at the undergraduate, Master, PhD, and Postdoc levels, as
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denotational correctness proofs as well as new probabilistic and differential inference algorithms) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and
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denotational correctness proofs as well as new probabilistic and differential inference algorithms) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and
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denotational correctness proofs as well as new probabilistic and differential inference algorithms) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and
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proofs as well as new probabilistic and differential inference algorithms) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable
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sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation
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of application. Proof of English proficiency About the department The PhD student will join CAES, a group working on the most efficient and effective computer architectures of the future, from large-scale data