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Apply advanced data mining, statistical modeling, graph algorithms, and machine learning to extract insights from large structured and unstructured datasets Mentor junior data scientists and analysts
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comparing models with entirely different structures and parameter counts, whether comparing linear regression against mixture models or decision trees. MML is strictly Bayesian, requiring prior distributions
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to: Quantum Computing Theory Quantum Algorithms Quantum Networking for Distributed Quantum Computing (As opposed to QKD) Quantum Machine Learning Quantum Sensing Quantum Applications Quantum-safe or Quantum
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languages (e.g. C/Fortran) Shared and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Serial and parallel debugging and profiling Parallel numerical
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detection; security of distributed systems, security of computer networks, privacy of networked systems, human-automation interaction and operation on networked systems and infrastructure; AI and computer
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topics as well as related topics (e.g., privacy, trustworthiness, mobile/wireless security, distributed learning and cloud security, software and system security). Areas of theoretical computer science
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candidate should be able to conduct research work independently To learn more about the work this group does, check out the following link: https://www.nrel.gov/grid/distributed-energy-resource-management
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Location ESRIN, Frascati, Italy Description Data Quality and Cal/Val Manager for Atmospheric Sensor Missions in the Sensor Performance, Products and Algorithms Section, Earth Observation Mission
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is driven by the increasing introduction of renewable energy sources (RES), both in large-scale installations (wind farms, solar) as well as distributed over large number of small-scale assets (e.g
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Research Infrastructure? No Offer Description Mission: Develop perception algorithms that allow estimating the state of a mobile robot; monitoring and presentation of results. Functions to be developed