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particular focus on data interoperability and on the integration of AI models, multi-agent systems, and intelligent workflows deployed across the Edge–Cloud–HPC Continuum. The research activities
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meteorological data and evaluate atmospheric model results - You will develop and apply methods for geostatistical interpolation of ultrafine particle concentration data - You will run models on HPC
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collaborative contraceptive discovery project. You will apply 'omics analysis, molecular simulations and machine learning to identify promising novel contraceptive candidates. You will strengthen your HPC and
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helping researchers in the planning/dimensioning and acquisition of specialized HPC systems, training incoming faculty on procurement processes, conducting requirement gathering to ensure hardware and
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to develop methodologies, models, and architectures for the implementation of Smart Ecosystems based on the integration of Digital Twins, Artificial Intelligence, and Edge–Cloud–HPC distributed
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) and data engineering for reproducible research. Familiarity with cloud/HPC workflows, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and
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) and data engineering for reproducible research. Familiarity with cloud/HPC workflows, containerisation (Docker), and basic bioinformatics pipelines will be preferred. Cross-disciplinary training and
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integration of Digital Twins, Artificial Intelligence, and Edge–Cloud–HPC distributed infrastructures. Research activities will include the design of Digital Twin architectures and platforms, the
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connect customer-facing sample management with traceable analytical workflows and research outputs. Information on the department can be found at https://globe.ku.dk . Our research The molecular
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: https://www.hds-lee.de/admission/openpositions/ Your Profile Mandatory qualifications are: M. Sc. degree in meteorology, physics, mathematics, or a related field Good knowledge in data handling and