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. Lähdesmäki. “Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport”. In: Proceedings of the 43rd International Conference on Machine Learning. OpenReview . 2026. What we offer
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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Summary The Department of Electrical and Computer Engineering at Ritchie School of Engineering and Computer Science at the University of Denver is looking to hire adjunct faculty to teach a variety of
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expectations: Prepare and facilitate course lectures and learning online or in-person. Maintain weekly office hours and consistent presence in assigned course(s). Model and promote critical thinking as
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include but are not limited to: AI-driven design workflows; machine learning and generative AI models; AI-based performance evaluation and simulation; agentic and multi-agent AI systems; human-AI
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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of interest supporting the instructional needs in our major, minor, and university-wide electives. Specific areas of need are spreadsheet modeling and analysis, machine learning, and project-based capstone
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modelling, automated neuroanatomical phenotyping, machine learning and advanced statistical approaches. The doctoral project will be developed jointly with the successful candidate and tailored
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. Duties/Responsibilities: 1. Data Management, Review, & Analysis (70%) Advanced Neural Signal Processing: Apply quantitative analysis, signal processing, and machine learning methods to high-dimensional EEG