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Field
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research. This exciting position offers a unique opportunity to develop cutting-edge Knowledge Guided Machine Learning (KGML) methods informed by ecosystem modeling of agroecosystem carbon and nitrogen
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research protocols and procedures, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where
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Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subjects of the research are: AI-assisted Bond Issuance, Causal
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, checking, recoding data for analysis). At least intermediate knowledge of SAS or R programming required. Knowledge of Python and/or machine learning helpful but not required. The University of Miami offers
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | about 4 hours ago
based on a combination of novel simulation techniques, Bayesian statistical methods and machine learning approaches. The successful candidate will work closely with Prof. Dr. Volker Springel, the director
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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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catalytic turbomachines—compact devices that combine chemical reaction and flow functions—using a novel machine-learning-based method, ChemZIP, to accelerate the modelling of complex catalytic and gas-phase
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Senior Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) Doctoral Degree or foreign equivalent degree. Three years of research experience in machine learning and
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to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods, with a focus on computer vision, to enhance wood
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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and