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Priorities: We seek applications across all AI domains, with emphasis on: Foundational AI : Machine Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers
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data, log-trace data from learning platforms, and panel data. Relevant areas of expertise include longitudinal data analysis, psychometrics, learning analytics, and machine learning. We are particularly
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machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based platform for the interactive and comprehensive evaluation of design solutions and mitigation strategies
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relational database environments Apply and evaluate methods from causal inference (e.g., confounding control, bias assessment, sensitivity analyses) Apply machine learning approaches for predictive modeling
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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Supervisor: Dr. Kamila Maria Jozwik, Jozwik lab PhD fees status: Home fees only (https://www.postgraduate.study.cam.ac.uk/finance/fees/what-my-fee-status ), 4 years Start date: October 2026 The
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Modelling, Applied Statistics, Linguistics, Data Analysis, Large Language Models, Machine Learning. Start date: 1st October 2026 Deadline: 30th April Duration: 36 months Funding: Funded Funding towards
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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About the Opportunity The Lecturer will teach introductory courses in architectural drawing, sketching, studio design, computer modeling, architectural history, technology, or project case studies