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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
Chemistry at the Institute of Materials Chemistry, TU Wien. The group develops and applies electronic-structure theory, machine-learning methods and predictive calculations of defects and transport properties
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which you will be automatically redirected to an external site after 5 seconds) Save job Click to add the job to your shortlist Send job Job Details Are you interested in using machine learning to
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computational pipelines for QTL data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web
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reactor. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the
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the development of knowledge graphs Development and application of AI and machine learning methods and pipelines. Qualifications Ideally, you hold a PhD in Data Sciences and have several years of
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data visualization, with a track record of designing and building visualization dashboards. Research experience in human-centered AI, or in the integration of AI and machine learning methods into
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Two postdoc positions in Thermofluid Design and Digital Modeling of Cooling Systems for Electroch...
process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design is both experimentally realizable and
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 1 month ago
project is conducted in collaboration with the deep probabilistic programming group of Thomas Hamelryck: https://di.ku.dk/english/research/groups/machine-learning-in-biology/?pure=en/persons/271052
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machine learning methods and pipelines. Qualifications Ideally, you hold a PhD in Data Sciences and have several years of experience collaborating with scientists in natural sciences, particularly
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-Intensive Systems group studies management and analysis of complex data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining