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partnerships needed to support local growth and resilience. Our work is guided by our purpose to impact people, place, resilience, and the environment. To learn more, please visit CED . Candidates must be
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communication systems, we encourage you to apply—even if you do not meet every item in the project description. We value candidates who are eager to learn, think creatively, and work across disciplinary
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, materials, and synthetic cells with embodied intelligence – chemical and physical – to endow them with the capacity to compute, adapt, learn, or make simple decisions. We are highly international and
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institution of research and higher education in the fields of technology and natural sciences. With over 26,000 students and more than 4000 scientists, research, teaching, and learning dedicated
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written; ▪ Willingness to learn new skills and take up challenges. A track record of publications in JCR-listed journals and/or participation in scientific conferences will be an additional asset
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PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
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, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with
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interest in data analysis, modelling, statistics, and machine learning. Experience in spatial data analysis (GIS), scientific programming (Python, R, or equivalent), or artificial intelligence will be
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heterogeneity govern transport dynamics and degradation mechanisms during extended operation. A coupled mechanical–transport framework, accelerated through machine-learning surrogate models trained on multiscale
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the institute and the academic community, a dedicated and passionate atmosphere prevails. The themes of Health and Wellbeing, Social-Cognitive-Affective Decision Making, Development and Learning, and Advanced