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are essential Additional qualifications Experience and courses in one or more subjects are valued: statistical machine learning, optimization, deep learning and signal processing. Rules governing PhD students
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their PhD. Project description The aim of this project is to deepen the fundamental understanding of machine learning through the lens of optimal transport theory, systems theory, and statistical physics
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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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to work at Uppsala University. Duties The PhD student will carry out research in signal processing and machine learning with a strong emphasis on theoretical foundations. The PhD student will actively
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future
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to knowledge in one or more of the following areas: machine learning, cybersecurity, or computer systems Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in
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addition, attention will be given to administrative, management and collaboration expertise. Qualifications required You must have: a PhD in microbiology, infection biology, or closely related relevant
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(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two