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Engineering (EEE), helping to develop algorithms and systems for disaster mapping and understanding geohazards in collaboration with space industries and responding agencies around the world. They will
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, aiming to explore and develop AI algorithms, frameworks, and hardware architectures for efficient edge deployment in vehicles, with a focus on neuromorphic computing. You will be part of the scientific TUM
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(“Autonomous System for Hybrid Hyperspectral-SAR Monitoring in Precision Agriculture”, Supervisor Prof. Hugo Hernández Figueroa, and “Development of Methodology and Robust Operational Algorithms for Hybrid
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, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in
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matter physics, and quantum computing. You will dive deep into the realms of theoretical and computational physics with a focus on the development of algorithms and large-scale numerical simulations. Your
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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University Abu Dhabi, seeks to recruit a motivated research or postdoctoral associate to lead the design, development, and validation of material, control systems, and algorithms for next-generation soft
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single needle, a robotic platform introduces complex motion control challenges that require the development of adaptive toolpath algorithm. This algorithm will ensure continuous and smooth deposition while
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groups are strongly encouraged to apply. Your Tasks: Development and application of algorithms for modelling, evaluation and visualization of ultrafast processes Investigation of ultrafast dynamics in
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computing resources and research equipment Opportunities for professional development and networking Collaborative and innovative research environment If you have any questions, please email Prof. Muhammad