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Field
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clouds through star-forming regions to planetary systems. Laboratory simulations under astrophysically relevant conditions will provide key insights into asymmetric photochemistry and post-irradiation
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applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud) Understanding of BMS architecture and electric mobility systems.
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in St. Cloud offers a wide range of patient experiences throughout students’ education in Greater Minnesota and prepares them to become exceptional clinicians and leaders for rural and immigrant
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/ML methods. Prior experience with analyzing real-world databases, especially claims and EHR databases. Prior experience with cloud computing. Strong programming skills using at least one of the
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. Experience with Linux/Unix environments, cloud computing, and version control systems (e.g., Git). Additional Information: Responsibilities: Perform comprehensive analyses of microbiome sequencing data (e.g
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QAA and QAOA Experience in cloud computing and building cloud computing infrastructure Interest and/or experience in developing and conducting lectures and/or trainings for QC Proficiency in writing
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knowledge in modern AI approaches such as knowledge-guided machine learning. Experience working with environmental or related data. Experience with supercomputing clusters and/or cloud platforms. Essential
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Aerosol and Cloud Microphysics group, part
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(edge to cloud), European Data spaces, SIMPL middleware, Interoperability Frameworks (e.g. Minimum Interoperability Mechanisms (MIMs), etc) If you additionally like to create results based on knowledge
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the last 0-5 years) in Atmospheric Science, Climate Science, or other climate-related science Expertise in any of the following: cloud and convection, severe weather, land-atmosphere interactions, impacts