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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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at scientific edge systems using large-scale HPC/AI computational and storage systems. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Evaluation of cloud data
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biostatistics faculty collaborating with the Childhood Cancer Survivorship Program (CCSP). You will develop innovative biostatistical methods for childhood cancer survivorship research and collaborate with CCSP
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. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API). Experience with airborne lidar data processing and canopy height modelling. We will place
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of advanced statistical methodologies, and supporting research on high performance and cloud computing. The successful candidate will also be expected to offer 2-3 advanced technical or methodological workshops
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2027 - 03:36 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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interactions, or aerosol–cloud interactions Strong experience in numerical modeling and high-performance computing • Experience applying AI/ML methods to model development, with strong programming skills (e.g
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, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications. The Signal Processing and Communications (SigCom) research group of SnT, headed by Prof. Symeon
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning