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Field
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program development with topics like abstract data types, trees, graphs, sorting, searching, greedy algorithms, and basic AI classification techniques. Students will gain both theoretical understanding and
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responsible for the end-to-end investigation of novel federated learning strategies for causal inference. The role will bridge rigorous theoretical work with hands-on algorithm design and development on real
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candidate will work on algorithm development for contact-rich robotic manipulation, integrating perception, planning, and control within a real-world robotic system. Job Responsibilities: Develop, implement
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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, focusing on the development of a mobile DC microgrid for military tactical applications. The role involves designing and implementing advanced control algorithms to coordinate multiple energy sources
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Computational Circular Design: Development, scalability and computational efficiency of surrogate-assisted many-objective optimisation algorithms for circular design for disassembly (C3.5-AMR
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of the developed algorithms) Empirical investigation of use cases Scientific exchange and publication of results This position offers the possibility to acquire a PhD degree, which is encouraged. This research
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with strong experience in learning-based control and mobile manipulation. The successful candidate will work on algorithm development for contact-rich robotic manipulation, integrating perception
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of computer science, data science, computational biology, and cyberinfrastructure to develop and refine research tools, pipelines, and software components. Responsibilities include designing and optimizing algorithms
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hyper-dynamic. Existing graph mining techniques struggle with this complexity and uncertainty, failing to yield actionable intelligence. This research project will develop next-generation, scalable