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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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processing, or networking (preferred). You have strong background in machine learning or deep learning (experience with deep learning frameworks such PyTorch and TensorFlow is a plus). You have solid
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, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. At Jane Street, our researchers, engineers, and
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highly collaborative research team to accelerate and extend ongoing research efforts (including DL-based joint species distribution modeling and causal machine learning) and lead methods development
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theory, Machine learning and multivariate statistics, Application in neuroscience, climate research, economics, ...). COBRA is a part of the Department of Complex Systems of the Institute
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multimodal generative AI for music/audio. Check out some of our recent projects here: https://dorienherremans.com/biblio (including work on models like Mustango, SonicMaster and other generative systems
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, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python) are required. Ability to communicate effectively in both
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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-making systems. Develop Advanced ML/AI Models for Air Quality Applications Applies machine learning (ML) and artificial intelligence (AI) techniques to enhance traditional chemical transport modeling
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve