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at Tilburg University, in collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, invites applications for a fully funded postdoctoral position focusing on predictive modelling
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an integrated framework for co-design and adaptive operation of electrical networks. DynConGrid develops real-time Model Predictive Control (MPC) for congestion management by reconfiguring topology, curtailing
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settings. The ultimate goal is to enable early, systematic, and robust screening of children at risk of neurodevelopmental disorders. Deep learning models typically produce point predictions, whose
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relevant to TCR prediction, including machine learning, molecular docking, and related modelling strategies. Experience in systematic literature review and the integration of computational findings with
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. The successful applicant will develop a predictive pipeline using atomistic modeling and machine learning to identify optimal "seeds" for directing crystal growth, followed by rigorous experimental testing
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behavioural predictions into the same framework, based on heterogeneous mental models which are used to evolve internal, imaginary scenarios within the robot. Indeed, the robot will ”imagine” multiple solutions
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Associate in Research The role involves developing and optimizing machine learning models to predict infectious diseases using multimodal health data. Responsibilities include analyzing correlations between
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to the development and refinement of analytical models, including predictive and spatial models, under the guidance of senior technical staff. The role supports translating quantitative outputs into meaningful
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, implement, and tune advanced control augmentation techniques (e.g., model predictive control, adaptive control) to enhance the stability and agility of COTS drones under dynamic conditions. Swarm Intelligence