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areas include the development of interpretable and trustworthy algorithms for Scientific Artificial Intelligence and active learning, integrating FAIR data management practices throughout the research
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environments (preferred). You possess the ability to conduct independent research and develop novel algorithms. You have strong analytical and problem-solving skills. You have a research-oriented mindset and
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are not limited to: Learn research techniques to develop algorithms and models for the simulation of field data Participate in experimental activities such as research design, data collection, technical
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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22 Feb 2026 Job Information Organisation/Company CNRS Department Laboratoire de physique de l'ENS Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage Researcher
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engagement—particularly within ESG disclosures—its implementation is currently challenged by ethical concerns regarding data privacy, algorithmic bias, and cultural resistance. This project aims to contribute
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analytical many-body calculations Expertise in one or more of the following: computational methods, software and algorithm development, high-performance computing, and data analysis Proficiency in relevant
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can