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responsibility is to conduct high-quality research on hybrid artificial intelligence. You will: Combine deep learning to capture long-term patterns and uncertainties with stochastic model predictive control
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climate experts with the aim to address existing uncertainties about climate feedbacks at the boundaries between oceans, land, ice, and atmosphere. Our interdisciplinary approach and state-of-the-art
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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regulations and product certification due to the inherent uncertainty of how AI systems make decisions. Classical engineering development guidelines, are difficult to interpret or simply not transferrable to AI
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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. The military supply logistics network faces uncertainty, which is dependent on the adversary and their means. The military supply logistics networks need to consider different scenarios, requiring the that it
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of Profs. Jack Middelburg and Henk Dijkstra , you will elucidate ocean alkalinity dynamics and develop new and improve existing models for ocean carbon cycling. The initial focus is on the alkalinity
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-leading climate experts with the aim to address existing uncertainties about climate feedbacks at the boundaries between oceans, land, ice, and atmosphere. Our interdisciplinary approach and state
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to investigate the cognitive and social behaviour (such as knowledge acquisition, organization, and transmission, recognition processes, or risk assessment and decision-making under uncertainty) involved in
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existing uncertainties about climate feedbacks at the boundaries between oceans, land, ice and atmosphere. Our interdisciplinary approach and state-of-the-art infrastructure will bring us forward in our