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Temporary contract | 36 months | Belvaux Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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) •Ref: 25-12•Fixed-term working contract at LISER for 36 months (extendable up to 48 months maximum)•Full-time, 40 hours/week •Department: Urban Development and Mobility (UDM)•Registration in the PhD
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the study of software engineering methods and approaches for quantum computing platforms. Successful PhD candidates will extensively explore and develop software security and software engineering techniques
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Temporary contract | 36 months | Belvaux Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology
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simulator studies. · Writing of research papers and publication of peer-reviewed journal articles. · Write a PhD thesis in the field of computer science and human-factors related topics
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: Luxembourg Institute of Science and Technology (LIST), Belval, Luxembourg · PhD enrolment: University of Luxembourg, Belval, Luxembourg Candidates shall be available for starting their position in 2025
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engineering Creating a teaching and learning environment for secure code principles and software vulnerabilities Engaging students with secure code principles through gamification PhD Student Role: Under
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I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
, the complexity of multi-dimensional data and the need for transparency pose significant challenges, which this PhD position aims to address via the very concrete case of simulated driving. You will
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operating guidelines for small-scale particle size classification technology and to produce a concept that can be developed as a payload. As a PhD student within LIST, you will have the following
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language models) against various threats that may occur in the real-world. Successful PhD candidates will extensively explore and develop software security and testing techniques for machine learning systems