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at the intersection of educational data science, AI in education, and the learning sciences, with additional advisory support from faculty and researchers across learning sciences, computer science, machine learning
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frameworks for quantum machine learning, including conformal quantum prediction and uncertainty quantification in quantum models; Theoretical and algorithmic advances rooted in statistical learning theory
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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and
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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image
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and decision-making in humans and machine learning systems. The post-holder will have responsibility for carrying out rigorous and impactful research into human-AI interaction and alignment, with a
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collaborate with other technical groups working on the design. The successful candidate will also have opportunity to conduct experiments and machine development activities on the existing accelerators. The key
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well as companies and governmental organisations . They will contribute to the activities of the wider machine learning and data science research group and write up the results of their work, with co-authors
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for individuals preparing for academic careers in statistics, biostatistics, machine learning, or related fields. The postdoctoral researcher will be supervised by Dr. Razieh Nabi. For inquiries, please contact
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Intelligence / AI/Machine Learning Particle Physics / Phenomenology , Phenomenology and Theory Appl Deadline: 2026/01/31 11:59PM (posted 2025/11/24, listed until 2026/05/24) Position Description: Apply