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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 22 days ago
decidable and solvable via a SAT-Solver. This approach has a major flow as it is not possible to be sure that the formula is satisfiable for larger models. Interestingly, communities in Knowledge
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data mining has allowed us to obtain insights from large amounts of data for decades, and it is worth
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interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data mining has allowed us to obtain insights from large amounts of data for decades, and it is worth
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research and above-average knowledge of Austrian labour and social law as well as good other legal knowledge (please enclose a complete transcript of records with your application!); excellent knowledge
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addition to technical and scientific knowledge, the candidate of choice will have excellent organizational and interpersonal skills, and thrive in a collaborative, fast-paced, and multi-disciplinary research setting. Our
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Requirements: Ph.D. in mathematics, applied mathematics, physics, computer science, engineering, or a related quantitative field. Strong knowledge of differential equations and applied mathematical modeling
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a comparable field of study Modelling experience in the field of water supply or drainage systems and/or data-based models desirable Knowledge of urban drainage, nature-based solutions (NBS), water
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or February 2026) Supervisor: Prof. Robert Sitnik, Dr. Vibekananda Dutta (co-supervisor) Project Overview: action This project explores semantic reasoning capabilities for intelligent robotic task execution by
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University, you will develop innovative methods to make geographic data smarter and more question-aware, contributing directly to the future of spatial reasoning and sustainability. Your job Answering