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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by
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to design adaptive, efficient, and intelligent algorithms for hearing assistive devices. Key objectives include improving speech perception in noisy and unpredictable environments, reducing listening effort
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary
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intelligent transportation systems (ITS), with an emphasis on developing and deploying state-of-the-art Large-Language Models (LLMs), Vision-Language Models (VLMs), and Vision-Language-Action (VLA) models
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Polytechnique de Paris, is one of France's top 5 general engineering schools. The mainspring of Télécom Paris is to train, imagine and undertake to design digital models, technologies and solutions for a society
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courses with minor algorithmic components and primarily programming courses with a focus on bioinformatics methods. Such graduate courses seek experienced bioinformatics, biotech, and data science
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visualization systems. Research themes: The PhD student will contribute to several of the following topics: Computer-generated holography (CGH); Optical system analysis and simulation; Developing AI/ML algorithms
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, particularly Python; (ii) use of parameter optimization algorithms, particularly PEST and PEST++; (iii) remote sensing applied to the water cycle; and (iv) application of machine learning techniques to spatio
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• Produce research products such as well-documented algorithms and code, software, and research publications • Prepare results for publications, work with collaborators in writing publications, and, in some
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How