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contribute to: Developing supervised deep learning algorithms for 3D point clouds Developing self-supervised deep learning algorithms for 3Dpoint clouds Expand for a wider variety of downstream tasks focused
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Your Job: Quantum computers will play a crucial role in the development and optimization of battery materials in the future. In this project, you will develop innovative quantum algorithms
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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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Assessment Systems: Toward Trustworthy AI for Complex Educational Evaluation Image and Video Analysis Using Machine Learning Algorithms Mathematical and Computational Neuroscience, from neural data and network
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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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; validating models using existing offshore datasets, lab-scale experiments, and collaborating with ongoing projects; developing optimisation algorithms for ensuring techno-economic feasibility of FPV systems
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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the entire system, where many interconnected modules affect each other. In this project, you will be designing algorithms to guarantee the reliable operation of semiconductor machines, together with a highly
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modern technologies is a highly active topic at the interface of fundamental research and applications. The development of quantum technologies has been identified as a national strategic area. Furthermore