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Bayesian computational methods for such (ill-posed) inverse problems and aims both at increasing their validity and at reducing their computational cost. In this project, we will focus on increasing validity
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inverse problems. The team aims at developing Bayesian computational methods for such (ill-posed) inverse problems and aims both at increasing their validity and at reducing their computational cost. In
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validation of the numerical model. Candidates should be holding a MSc degree in Engineering (or equivalent), with demonstrated experience in computational fluid dynamics (CFD), preferably in hydraulic
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What do we expect from you? You must a hold a PhD degree in Political, Social or Communication Sciences, (Digital) Humanities, Media Studies, Computational Social Sciences, Data Sciences, or a
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& Expertise Strong background in AI/ML methods with emphasis on explainable AI (XAI), interactive explanations, and human-in-the-loop AI systems. Experience or strong interest in Human-Computer Interaction (HCI
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Reasonably Achievable) strategies, enhancing radiation safety. The goal of this project is to to make computational methods ready for official dosimetry, specifically for neutron, high energy and pulsed fields
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Department: Department of Computer Science Regime Full-time Let’s shape the future - University of Antwerp The University of Antwerp is a dynamic, forward-thinking, European university. We offer
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, Coastal Engineering, Mechanical Engineering, Hydraulics, Geosciences, or a related field Strong background in hydrodynamics, sediment transport, and numerical modeling Experience with computational tools
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Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Let’s
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sinks of atmospheric constituents. For this research, the Institute uses spectrometric observations from the ground and from space, as well as specific numerical models. The atmospheric constituents