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-based reasoning strategies for oncology, including tool-augmented inference, multi-agent or compound model workflows, process supervision, verifier-guided training, and reinforcement learning-based post
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causal analytical foundations of mass transit system performance. The research is expected to contribute both novel methodological advances in statistical modelling, causal inference, and machine learning
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine
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your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
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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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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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platforms a plus Experience applying machine learning, artificial intelligence, and large language models to research a plus The anticipated start date is September 1, 2026. The postdoctoral position incoming
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of Singapore, and EPFL (Switzerland). These partners are looking for talents in several domains of machine learning, AI, computational biology, and biology, to develop PhD theses across the main pillars
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the