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Information in particle physics and cosmology AI/Machine Learning Starting Date: 2025/12/05 Appl Deadline: 2026/01/05 08:59AM (posted 2025/12/04, updated 2025/12/02, listed until 2026/01/05) Position
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn mathematical modelling of hormone rhythm
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-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts
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motivation, which includes your preference for performing theoretical and/or algorithmic research (max 1 page); a list of publications or prior projects (max 1 page); the names and email addresses of two
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applications for a Research Assistant Professor position. We seek candidates whose research examines how increasingly agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and
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Health, Medical Sensors, Systems Physiology, Internal Medicine Secondments : University of Ulm (D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning
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to seamlessly integrate complex hormonal data, high-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms
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algorithms for inference and decision-making by pushing the boundaries of computational techniques. The research emphasizes efficiency in resource and data usage, reducing environmental impact, and ensuring