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, candidates with research interests in areas such as Bayesian methods, survival analysis, experimental design, functional data analysis, clinical trials, precision medicine, and meta-analysis are especially
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(e.g., Bayesian inference, deep learning), ideally connected to spatial omics, and experience with frameworks like PyTorch, Keras, Pyro, or TensorFlow Application process: Interested candidates should
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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods
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California State University, Northridge | Northridge, California | United States | about 1 month ago
Hawaiian or Pacific Islander. For more information about the University, visit: http://www.csun.edu About the College: For more information about the Department of Psychology, see: https://www.csun.edu
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subjects related to Mathematics for Economics, specifically in the Bachelor's Degree in Economics (subjects: Mathematics for Economics I, II, III, and IV, and Bayesian Methods). Additionally, the candidate
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& Partnerships (NSF-TIP) directorate. More information on the project is available at: https://industriesofideas.ai/ . Term-limited: This is a term-limited position for two years, with the possibility of renewal
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. We are interested in candidates with research interests in causal inference or Bayesian methodology, and we also welcome strong applicants from the broader fields of statistics and machine learning
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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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designs such as observational study, randomized clinical trial, adaptive randomizations, Bayesian analysis of randomized trials, conventional meta-analysis, meta-regression, and network meta-analysis Work