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Field
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of the molecular ISM of galaxies, with a focus on galaxy centres. In particular, this project aims to measure the spatially resolved properties of giant molecular clouds and/or weigh the supermassive black holes
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Qualifications:. PhD in one of these fields: Computer Science, Data Science, Biomedical Informatics, Computational Biology, Information Science or a related field. Experience in at least one of the following
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to the project): PhD in Computer Science, Distributed Software Architectures, Artificial Intelligence, or a related discipline. Strong research background in data management, including policy governance or data
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experience in cloud computing and utilizing data from the All of Us Research Program are particularly well-suited for this position. Outstanding U of A benefits include health, dental, vision, and life
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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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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
investigate together the chemical and physical evolution of the interstellar medium and star- and planet-forming regions, from clouds to disks, with links to exoplanets and our Solar System. The start date is
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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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. 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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: Programming proficiency in at least R or Python (ideally both), plus comfortable use of Unix/Linux shell. Hands-on experience with high-performance computing (Slurm/PBS or equivalent) and/or cloud computing
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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