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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 includes both
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the Department of Information Technology website . At the Division of Systems and Control , we develop and analyze both theory and concrete tools to design systems that learn, reason, and act in
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and computational work
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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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optimization, AI, power electronics with good publication record· Good at coding in python with different DRL algorithms training, or good at digital platform development will be a preference Knowledge of
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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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part of the WASP Graduate School including following its curriculum. The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary
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revolution in the field of legged robotics and their successful custom deployment in various applications. Project overview The aim of this project is to develop a software framework for AI based Holistic Co
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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics