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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 9 days ago
(Loreley, CEDAR and MAGELLAN). This project aims to design and develop an open-source management solution for a federated and distributed data exchange platform (DXP), operating in an open, scalable, and
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Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large foundation models (e.g., LLMs and VLMs
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& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
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and democratic participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal
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- manufactured Ni₃Al intermetallic alloys that integrates residual stress considerations directly into the design process. The research will focus on the development of topology optimization algorithms capable
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size, weight, power and cost constraints, accurate relative positioning and motion knowledge across platforms, coordinated data acquisition strategies, and the development of SAR image formation
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are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a
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. The studentship will start on 1st October 2026. Project Description Project Aim To develop and validate an AI co-pilot software system integrating multi-modal radiomics data to enhance cancer detection speed and
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are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a
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to enable drug discovery applications”. Are you interested in mapping the binding sites of the human proteome and developing new pharmacophore software to screen against the sites to identify novel bioactive