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learning based optimization algorithms, human and AI coordination in best decision making for urban transportation related problems. The role will focus on developing generic frameworks and innovative
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systems that are both scalable and explainable. This role bridges algorithmic research and systems implementation, offering opportunities to collaborate with leading academics and engineers on developing
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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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developers who work together to solve problems in the following areas: Counter AI Research: Study threat models targeting AI and ML algorithms, understand the behaviors of AI algorithms, identify weak points
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assist in developing quantum reservoir computing algorithms and work using them to model power systems data from, in particular, NLR’s ARIES platform, to explore the limits of quantum reservoir computing
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unsupervised techniques, time-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple
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) will contribute to a two-year applied research project funded by the BCA, focusing on the development of a power grid interactive building or cluster of buildings. The role involves designing and
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privacy constraints, robust solutions are essential. This PhD project will develop methods for building reliable medical imaging models that generalize across distribution shifts without retraining
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. The QUBIC consortium will deliver disruptive innovations across three core quantum domains: Development of quantum algorithms to solve current industry-specific challenges. Advancement of quantum processors
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candidates must thus have a strong interest in algorithmic development as well as embedded hardware integration. Role and responsibilities This PhD project will be executed in close cooperation with