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Field
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. By integrating cutting-edge multi-agent systems, federated learning, and game theory, this project will develop sophisticated decentralised algorithms that enable autonomous vehicles (AVs
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analysis, and algorithms of computational research questions at a level sufficient to converse with Princeton's world-class researchers to support the ongoing work. This will consist of independent research
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nanocrystal morphology and optical property characteristics. The researcher will work collaboratively with graduate student(s) to design and implement a machine learning (ML) algorithm using the database as
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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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technical subjects such as programming, data science, machine learning, and algorithmic fairness is highly desirable. Candidates must have teaching experience in a degree-granting program, including lecture
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need. Apply AI and machine learning algorithms to software engineering projects in the researcher’s specific domain. Application of Domain Expertise Initiate and maintain open collaboration with
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discovery with a strong emphasis on domain-driven impact. Develop, optimize, and transition algorithm prototypes to robust implementations Work with ORNL researchers, as well as internal and external project
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Position Location: Odense, 5230, Denmark [map ] Subject Areas: Pure math with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. Appl Deadline: 2025
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assistance systems Collaboration in the development of AI algorithms (LLM, fine-tuning, RAG, AI agents, embeddings) Literature research on the topic of AI What you bring to the table Studies in
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems