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areas: Development algorithms and their software implementation for ROS in C++ and Python with focus on robot navigation and communication. Field deployment and experimental evaluation in harsh
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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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space)? What are appropriate descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms
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(LLM), and optimization algorithms. Collaborating with our team to transform research insights into practical, impactful solutions. Staying abreast of the latest advancements in ML, transformers, graph
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experience in radar research, developing signal processing algorithms for long-range ultra-broadband Synthetic Aperture Radar systems and short-range FMCW systems. In recent years, breakthroughs in
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at the Faculty of Engineering and contribute to cutting-edge research in radar systems. The radar group at BTH has extensive experience in radar research, developing signal processing algorithms for long-range
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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. You have a strong ability to solve problems and formulate algorithms. You also have an interest in genetics and genomics. You are organized, proactive, and can work independently as
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the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software
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, use imitation learning algorithms to learn pick-and-place actions, design HRI experiments with users, evaluate data, and share the code and benchmarks in open repositories. This postdoctoral position is