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/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its
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Are you interested in exploring how multi-agent aerial manipulation can contribute to construction and working at the intersection of robotics and machine learning? Job description Advancements in
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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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systems and control, applied mathematics, engineering, or a related field A strong background or interest in systems and control, applied mathematics, machine learning, and affinity with biological systems
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design and characterise reconstruction methods—both machine-learning-based and traditional—for the bundles of muons that reach the detectors, and apply them to data and simulations to constrain cosmic-ray
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, they have the potential to solve certain computational problems far more efficiently than classical machines. Realizing this potential requires entirely new numerical algorithms that combine advances in
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closely related discipline). You have a strong interest in AI/machine learning, data mining, regression analysis, responsible AI, causal inference, and programming (R/Python, SQL). Moreover, you are driven
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independently. We value personal development: you will receive training in advanced computational techniques, machine learning, data analysis and scientific communication. You’ll have the opportunity to attend
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20 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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proficiency: IELTS = 6.5 (academic) or TOEFL computer-based = 237 or TOEFL internet-based = 92. Additional Information Benefits What can you expect from us? 232 vacation hours per year, based on a 38-hour