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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
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. Job Description: A postdoctoral position is available in the laboratory of Catherine Marcinkiewcz, Ph.D. at the University of Florida. Research in the Marcinkiewcz lab focuses on unraveling neural
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knowledge about recent neural network architectures for machine learning (e.g., CNNs, RNNs, GANs) have considerable experience with a deep learning framework are curious about the cross-field between signal
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neural network models, produce stimuli for artificial and biological agents, participate in experiments with chicks maintained in the Biological Services Unit, contribute to lab meetings and research
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) experience with neural network training and language model fine-tuning; (2) background in natural language processing, linguistics, and/or human reasoning; (3) strong coding skills; and (4) strong
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well as in designing coordination strategies for them. Our recent work on RL and graph neural networks (GNNs) demonstrate some of our key research directions relevant for this position. A high degree of self
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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NORPOD is a collaborative postdoctoral program of the Nordic EMBL Partnership for Molecular Medicine . The partnership is a network of four national research centers across the Nordics and the
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contributes advanced tools for spatial molecular phenotyping, including smFISH-based spatial transcriptomics, spatial validation of single-cell data, and gene regulatory network mapping during neural