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, artificial gauge fields , Artificial Intelligence , Astronomy , Astronomy and Astrophysics , Astroparticle Physics , astrophysics , Astrophysics (astro-ph) , Astrophysics Computational , Astrophysics
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: - Have (or be close to completing) an MSc in computer science or a related field. - Have an interest in both theory and practice. - Have strong programming skills and interest in developing state
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within a Research Infrastructure? No Offer Description About the school: The school aims at bringing highly qualified and motivated graduate students to the forefront of the field of Multimessenger
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: Have (or be close to completing) an MSc in computer science or a related field. Have an interest in both theory and practice. Have strong programming skills and interest in developing state-of-the-art
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using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out the methods and
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, profilometry and AFM. You should also be familiar with theory of plasma discharges and have the background required to extract plasma parameters from plasma diagnostics data and with methods to perform time
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methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as well as programming to test out
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) have some exposure to (hyper)graph theory, network science, and/or reaction mechanism/CRN studies. Candidates who do not meet all of these criteria should not feel discouraged. If you are interested in
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or comparable fields Good knowledge of quantum theory, ideally quantum information theory Organizational and communication skills Ability to work independently in interdisciplinary teams Good written and spoken
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-resolved mass spectroscopy and should be versed in materials characterisation methods including XRD, nanoindentation, profilometry and AFM. You should also be familiar with theory of plasma discharges and