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Field
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research and innovation agenda by: Conduct applied or fundamental research and publish the results in high-quality conferences and journals; Developing Computational Intelligence (e.g., Machine Learning and
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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Torr on linkedin: https://www.linkedin.com/in/philip-torr-freng-frs-1085702/?originalSubdomain=uk Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a
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23 Jan 2026 Job Information Organisation/Company IMT Atlantique Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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closely related field PhD training covering topics such as computational modelling, numerical methods, statistical analysis, machine learning or data-driven analysis of complex systems Experience 0–3 years
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems
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network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce using UPSC transformation and somatic embryogenesis pipelines; evaluating drought
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collaboration. Qualifications: Applicants must have a PhD in Robotics, Control Engineering, Machine Learning, AI, Mechanical or Electrical Engineering, or a closely related field. Strong focus on robot
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be also encouraged to explore other research opportunities or collaborations within the group. Tools and techniques to be developed include but are not limited to MR pulse sequences, machine learning