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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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open up exciting career opportunities? Are you interested in cable technology and condition monitoring and do you have a strong competence in signal processing and machine learning? As a PhD candidate
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, execution efficiency, and live trading performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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of the detector upgrade. The LPC is also a major hub for Machine Learning developments for particle physics. There is close and frequent collaboration with the Fermilab theory community. The LPC provides
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot
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of models in existing simulation software conducting numerical studies, also on HPC systems Further specific tasks can be tailored to the attitude and interests of the PhD students/postdocs. Requirements