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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 21 days ago
/Administrative Internal Number: 25565 POSTDOCTORAL ASSOCIATE, McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, to develop computational circuit models, analytical theory, and
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programs-ranging from national infrastructure to major technological rollouts. The project focuses on developing intelligent decision architectures, predictive analytics, and adaptive computational models
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reputation and publication record in consciousness science, psychedelic science, predictive-processing, computational modelling, and integrative theoretical work. You will have a proven track record of
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research communities. Applicants are invited to propose a research project around the development of AI models for predicting promising catalyst candidates to integrate molecular modelling techniques
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Veterinary Medicine ● Variant discovery and genome annotation: Apply deep learning and graph-based models to improve variant calling, transcriptome annotation, and functional prediction in veterinary-relevant
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction, or decision-making in autonomous driving or robotic
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and to characterize interactions with fire regimes. Ultimately, these results will also contribute to a combined paleo-modeling approach at the core of the RETROPEST project (https://anr.fr/Projet-ANR
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, Python, and SAS or Stata) • Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling, experience with Medicare claims data • Clear scientific writing and
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database modeling, creation and implementation of functionalities and interactive interfaces, case study development and analysis, and repository management and documentation of technological processes