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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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related to modeling and simulation of biological systems, 3) very good IT skills, in particular the ability to program in Python, 4) very good knowledge of machine learning methods, neural networks, and
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for the 2027-28 academic year. Qualifications We invite applications from those who hold a PhD (or equivalent) or expect to complete the requirements for a PhD in finance by July 1, 2027 or soon thereafter. (We
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beginning in the 2027-28 academic year. Qualifications We invite applications from those who hold a PhD (or equivalent) in the relevant field(s) or expect to complete the requirements for a PhD in accounting
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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testing of deuterium permeation experiments in support of the UKAEA’s LIBRTI project (https://ccfe.ukaea.uk/programmes/fusion-futures/librti/). This will include expanding capabilities on UoM’s Gas-Driven