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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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interested are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Analysis of CRISTALair Functional Flight Campaign Data Due to climate
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processes that could be realised in neuromorphic hardware. The research will combine theoretical derivation and simulation-based validation, using mathematical modelling, algorithmic experimentation, and
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or related fields past experience with Machine Learning algorithms and systems past experience with robot control and operation programming experience with ROS, C/C++, Python and/or PyTorch experience in
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developments, algorithmic implementation, and analysis. Experience with electronic structure and dynamics, non-adiabatic molecular dynamics, and coding is strongly selected for. Please seehttps
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developments, algorithmic implementation, and analysis. Experience with electronic structure and dynamics, non-adiabatic molecular dynamics, and coding is strongly selected for. Please seehttps
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, and analysis by using concepts and methods from machine learning, including pattern recognition, graphs, and complex networks. ** Specific Research Areas: * Develop concepts and algorithms to analyze
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used by the research team and will test the algorithms already developed by the laboratory and improve them on the basis of their performance to recognise drug induced cell morphologies About You You
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provide large and complex datasets. By applying advanced pattern recognition and clustering algorithms, the aim is to automatically detect coherent spatial domains. These domains represent regions with
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mathematical statistics, machine learning, coding, and algorithmics. Contribute to programme design, accreditation, and innovative teaching strategies that enhance student experience and employability. Research