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phenomena across scales, combining multiple fields including physics, mathematics, astronomy, history & philosophy of science, and social science. Its approach to societal engagement throughout the project’s
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of Technology. At each location we bring together more than 150 staff members. In ScaDS.AI, various research topics are being worked on within the framework of a graduate school on the fundamentals and
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
. In this project, you will use whole cell mathematical models (WCMs) to generate predictions about evolutionary outcomes under defined conditions, then design and run bacterial evolution experiments
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/Alzette (Belval) 1511, Luxembourg [map ] Subject Area: Mathematics Appl Deadline: (posted 2025/01/16, updated 2025/02/06, listed until 2025/07/31) Position Description: Apply 2025/07/31 11:59PM Position
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of Economics and Management Faculty of Mathematics and Natural Sciences Faculty of Organic Agricultural Sciences Faculty of Civil and Environmental Engineering Faculty of Mechanical Engineering Faculty
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available
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master’s degree or diploma in physics, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including