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- KTH Royal Institute of Technology
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position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Computer Science We are looking for two highly motivated individuals to pursue a Ph.D. in algorithms
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using suitable algorithms We expect excellent communication skills (English, spoken and written) and ability to interact efficiently in a team. Further information The position is fixed term according
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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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develop new algorithms where needed: this may include the incorporation of genomic or other omic data 2) An important second part of the post is helping to automate components of interpretation and
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comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial
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through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and techniques to cope with real-world challenges including but not limited to uncertainty, physical
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, or equivalent, with excellent knowledge of digital communications and signal processing. High grades in the core courses are required. Skills in mathematical analysis, modeling, and network algorithms
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on Bayesian methods for real-time, risk-aware trajectory planning in autonomous driving. Develop, implement, and evaluate algorithms for scenario pruning, control action selection, and reachability analysis
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driving. Develop, implement, and evaluate algorithms for scenario pruning, control action selection, and reachability analysis. Compare advanced deep learning–based methods with probabilistic approaches