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closely related discipline). You have a strong interest in AI/machine learning, data mining, regression analysis, responsible AI, causal inference, and programming (R/Python, SQL). Moreover, you are driven
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engineering stimulated by recent developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with
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, or hold an equivalent qualification that allows enrollment as a PhD student at the University of Vienna by that date. Because we design and build our research machines ourselves, you must have extended
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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a mixture of computational, analytical and machine learning approaches to model the heat transfer to fuels and their physical and chemical behaviour, including changes in chemistry and physical
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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developments in machine learning, the project investigates how runners’ shared social identity can influence their movement synchrony, physical load, and interaction with the running infrastructures. Using
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position in Toxicology We are looking for a motivated PhD student to join our team
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, Machine Learning, or Smart Energy Publication record in peer-reviewed journals or conferences, commensurate with stage of career Good programming skills in Python, R, Java, or Matlab Experience