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Field
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, Mathematics, Physics, Engineering, Computer Science or related disciplines with a strong academic record. Strong background in data analysis, statistics, machine learning, scientific computing, or related
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Norwegian University of Life Sciences (NMBU), within the Faculty of Science and Technology(REALTEK), invites applications for a PhD position in Applied Causal Machine Learning. The position is affiliated with
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of expertise Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think and learn than what you currently know. PhD or other research
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and large models, limiting real-world deployment. This PhD focuses on efficient Physical AI, emphasising data-efficient training, reinforcement learning, continual adaptation and edge deployment
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7 Jul 2026 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering » Computer engineering Researcher Profile Other Profession
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include the development
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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
interacts with the prefrontal cortex to integrate interoceptive signals and guide higher-order cognition. Combining ultra-high-field layer fMRI at 9.4 Tesla, diffusion MRI, and machine learning in humans with
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20 Aug 2026 Job Information Organisation/Company Amsterdam UMC Research Field Biological sciences » Biological engineering Researcher Profile First Stage Researcher (R1) Application Deadline 1 Sep
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current