660 algorithm-development-"Newcastle-University"-"Newcastle-University" positions in Sweden
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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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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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interpretation of results. You will also tailor these analyses in response to clinical and researcher feedback, and help develop new algorithms where needed: this may include the incorporation of genomic or other
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properties. In this project, we will apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and
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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
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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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apply machine learning and optimization algorithms in order to achieve the design of such nanophotonic structures. As a postdoc you will be part of the Condensed Matter and Materials Theory division, a
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optimization approaches will be developed. Main responsibilities Your major responsibility as doctoral student is to pursue your own doctoral studies. You are expected to develop your own scientific concepts and
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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