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Officer will be mainly responsible to process geophysical data and analyze the data using machine learning algorithms. The position involves in conducting research, supervising undergraduate students, and
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of fairness, safety, and privacy in digital technologies. Key Responsibilities: Conduct research and development in trust technologies – translating algorithms into tools and frameworks and implementing working
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, including: asymptotic enumeration of (hyper)graphs with highly irregular degrees; distribution of small subgraphs in random (hyper)graphs with highly irregular degrees, and extensions of these considerations
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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NSF funded projects, advancing the knowledge about distributed systems, developing novel algorithms for distributed resource and workload management, simulating and emulating systems, as
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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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studies for project-based research topics. Contribute to the development of algorithms and models to enhance the reasoning abilities of large language models in the healthcare domain. Job Requirements
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CEE 1505/2505 - Adjunct Faculty Civil & Environmental Engineering - Pennsylvania-Pittsburgh - (25003651) CEE 1505/2505 - Water Treatment and Distribution System Design The University of Pittsburgh