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questions. Implements and adapts machine learning and AI-based approaches for high-dimensional epidemiological data, including variable selection, prediction modelling, and data integration. Retrieves
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Compiling and analyzing information and using predictive modeling. Identifying and defining problems/alternatives and developing recommendations for leadership decisions Planning, organizing, and implementing
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, MES, APC). In-depth research in areas such as Reinforcement Learning, Large Language Models, Digital Twins, Predictive Maintenance. Overseas research experience or experience collaborating with industry
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, concerning the life cycle management of turnouts. The goals are: To develop different mathematical models for turnouts’ aging curves. To gain a clear understanding of the main parameters influencing the curves
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an intense of microbial activity contributes into the process of stabilization of organic matter; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict
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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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. BDI is based at the Princeton School of Public and International Affairs (SPIA), co-hosted by the Empirical Studies of Conflict (ESOC). For more information, please visit our website: https
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Research Technician II - Psychiatry - Behavioral Medicine - Collective for Psychiatric Neuroengineer
activity across large-scale cortical and subcortical brain networks. By integrating mouse models with approaches from psychiatry, neurophysiology, molecular biology, and biomedical engineering, our research
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production, recycling and value chain optimisation. The research focuses on applied AI in areas such as sensor data analysis, time series modelling, automation and decision support, with strong links
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measurement science research in robotics, advanced autonomy, and artificial intelligence systems. Utilizing deep learning, large language models (LLMs), reinforcement learning, and unsupervised machine learning