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Data Scientist (Artificial Intelligence). We now invite applications for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models
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; mechanism design and institutional design; cooperative AI and multi-agent systems; the study and development of large language models; cross-cultural psychology and large-scale behavioral data; philosophy
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functional genomics, bioinformatics, and machine learning to support the generation, interpretation, and screening of large-scale experimental and computational outputs. The successful candidate will
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landscape constrains or enables discovery. The project draws on tools from topological data analysis (e.g., persistent homology, Euler characteristic curves, discrete curvature), machine learning (e.g
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quantitative expertise in one or more of the following areas: human decision making; decision modeling; human-machine interaction; human perceptions of AI; large language models; data simulation; machine
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. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management
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: research experience in skin biology, tissue repair, reparative medicine, epigenetics, or RNA biology experience in multi-omics integration, advanced statistics, machine learning, or biological data
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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to efficacy, safety, and value is essential. The successful candidate is expected to develop and lead independent research using advanced econometrics, predictive analytics, and machine learning, including
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Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and