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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
to semantic pipelines and algorithms, data models, ontologies, and semantic data harmonization and integration strategies for a variety of translational research contexts, including the following data types
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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. This position requires a deep understanding of the Rust programming language and agility working with the core concepts therein, proficiency in algorithm development with a focus on optimization via profiling
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) - Isabel.neatrour@newcastle.ac.uk Weblinks: EJS ACT-PD study: https://www.ejsactpd.com/, Brain and Movement Research Team: http://bam-ncl.co.uk/ The Institute is part of the Faculty of Medical Sciences which holds a
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Code 9791AO Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Job description: 50%: Lead and conduct research in the development and application of algorithms
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. Cleaning, structuring, and annotating the data needed to train and validate AI models. Development of AI modules and alert systems: Development and integration of algorithms for analysis, anomaly detection
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“algorithmic bias” in AI systems; understanding what it would be to “align” AI systems with ethical norms; developing and evaluating proposals for the governance of powerful AI systems; the ethical issues raised
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types. Your algorithms will first be evaluated through simulation using real operational datasets, and later deployed and tested at two physical facilities: a kW scale testbed at TU Delft’s Green Village
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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an interdisciplinary and international environment. Candidates should send their applications by April 30th through https://cv.newton-6g.eu/ Incorporations will begin in May 2026. DC1: Data-driven models for CF networks