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data analysis is required. The lab mostly uses R for data analyses; knowledge of R is not required, and the postdoctoral scholar will have the opportunity for mentorship and learning. To Apply: Motivated
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 10 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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, and mentor graduate and undergraduate students, and may also teach one course per year for the Department of Statistics. A Ph.D. in Statistics, Biostatistics, Machine Learning, or a directly related
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for the postdoctoral position based on official transcripts and other documentation as required. If the candidate(s) will teach during their appointment, then additional teaching credentials are required. UNC Wilmington
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computational models, applying statistical and machine learning methods, and integrating data across modalities to generate novel scientific insights. The Postdoctoral Fellow will lead manuscript preparation
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of LCA methods and tools. • Familiarity with energy–water–land interactions, environmental impact assessment, or infrastructure planning. • Machine learning or data-driven methods for large-scale
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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Materials Required: Further Info: https://argonne.wd1.myworkdayjobs.com/Argonne_Careers/job/Lemont-IL-USA/Postdoctoral-Research-Associate---Machine-Learning-in-High-Energy-Physics-Detector-Operations_421270
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data, log-trace data from learning platforms, and panel data. Relevant areas of expertise include longitudinal data analysis, psychometrics, learning analytics, and machine learning. We are particularly