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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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models and algorithms in Python, with documented experience in PyTorch. The applicant should be knowledgeable with neural networks and furthermore have a strong drive towards performing fundamental
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quantum spectroscopy, sensing, photonics, semiconductor quantum optics, quantum materials, and quantum algorithms. Postdoctoral Fellows will collaborate with at least one QRI Fellow Mentor. Eligibility
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believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities: Teach
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believe software is a systems engineering challenge rather than a coding problem. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities: Teach
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
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Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance the understanding of high-dimensional neural activity patterns. The successful