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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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perturbations. Climate and human-induced disturbances may alter forest ecosystems dynamics, modifying eventually their resilience to rapidly changing conditions. Previous studies based on the temporal analysis
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commercial simulation tools such as Abaqus and Comsol Multiphysics. o Familiarity with multi-scale or coupled field analysis (e.g., structural-electromagnetic, fluid-structure). o Understanding of drone
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analysis (R, Python) is an asset. Curiosity, creativity, rigor, willingness to learn, team spirit and collaborative capacity, excellent time and priority management. Fluency in English (written and spoken
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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical
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, and multi-level data analysis Communicate and collaborate with a research team, including teachers and student assistants Engage in international opportunities for learning and development (i.e
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instruments (e.g. Thermo Orbitrap technology). Experience in using (AP-)MALDI technique for analysis and imaging. Experience in LC/MS for targeted or untargeted studies is an asset Ability to execute research
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framework to bridge this gap and enable organizations to confidently deploy secure GenAI solutions by evaluating the machine-learning models intrinsically, identifying components of an AI pipeline and their
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, and Machine Learning/AI 5G on organisations from both the private and public sectors
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21 Aug 2025 Job Information Organisation/Company University of Luxembourg Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Luxembourg