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for vulnerability detection, conducting rigorous testing to ensure accurate assessment of model robustness against adversarial attacks. Is Your profile described below? Are you our future colleague? Apply now
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, as well as designing, testing, and debugging to improve software quality across domains such as FinTech, energy, and Industry 4.0. Within this context, the PhD will contribute to the group’s growing
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware
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! ESRIC is conducting activities in three main areas: Research and testing facilities, Business support and incubation, and Community management. The primary objective of ESRIC is to research, develop and
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Networks for MLFFs Implement and test uncertainty-aware loss functions Study calibration and post-calibration for predictive uncertainty Integrate uncertainty modules into MLFF architectures Detecting
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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected