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Field
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An already acquired Phd in Electrical Engineering, Computer Science, Applied Mathematics, or a relevant field Affinity for formal and simulation models, as well as algorithmic solutions to problems
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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). Experience collaborating with educators or educational institutions on applied research projects. Ability to bridge technical and pedagogical perspectives, translating between educational needs and algorithmic
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members. Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous
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. The current position deals with free-space optical transmission experiments. It will involve challeges with low SNR, atmospheric turbulence issues, coherent recevers and related signal processing algorithms
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to the application deadline Experience from sea ice field work or polar expeditions Experience in work with oceanographic or meteorological data and models What you will do Apply, validate and improve algorithms
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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, fined tuned for zooming in on machine spatial reasoning, is within the scope of this project. Developing efficient algorithms for converting computer simulations of a system in a complex environment (e.g
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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: Research (65%) · Investigate literatures to identify existing solutions and the problem · Develop and apply state-of-the-art natural language processing algorithms and models to multimodal