466 distributed-algorithm-"Newcastle-University"-"Newcastle-University" Fellowship positions
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- LE STUDIUM LOIRE VALLEY INSTITUTE FOR ADVANCED STUDIES
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-efficient computing Developing mathematical modeling for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer
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and optimisation algorithms, focusing on their practical application in the context of the RaceEngineerAI project. Tasks include: - Developing models capable of simulating the behaviour of racing
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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affiliated with the Center of Excellence Integreat . The position is for a period of four years. The nominal length of the PhD program is three years. The fourth year is distributed as 25 % each year and will
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work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is to build and validate edge-assisted offloading strategies, complete with software APIs, through
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with the Center of Excellence Integreat . The position is for a period of four years. The nominal length of the PhD program is three years. The fourth year is distributed as 25 % each year and will
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existing tools and databases into high-throughput pipelines, and facilitate the display and the distribution of processed data. Related projects and responsibilities will include: Statistical analyses
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
Develop and implement novel AI models and learning algorithms for multimodal and generative modeling. Collaborate with neuroscientists, clinicians, and AI researchers on interdisciplinary problems involving
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Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and
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unify programs and curricula in data science with an initial emphasis on questions grounded in data that are generated by human activity, including computational social science (e.g., algorithmic