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Field
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existing studies, lake model simulations for emulator development and calibration. Use the emulator in a Bayesian statistical framework to quantitatively interpret paleoclimate proxy time series. Lead
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methods of Bayesian inference as relevant to the assigned atmospheric modeling. Expertise with computational implementations of atmospheric radiative transfer, on Linux-based workstations and large High
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well-qualified candidate for this position will also possess: Working experience with Bayesian analysis and MCMC. Bayesian Modeling. MCMC computation. Bioinformatics. Clustering. Salary: Compensation
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 14 hours ago
, noninferiority trials, multiple endpoints, adaptive designs, Bayesian design and analysis methods, estimands, meta-analyses, benefit-risk analyses, subgroup analyses, biosimilars, patient experience data
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Assistant Professor positions beginning August 16, 2027. We seek outstanding candidates with research interests in causal inference, Bayesian computation, statistics, machine learning, or related areas
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genomic or molecular datasets Background in Bayesian statistics, causal inference, or probabilistic modelling. Familiarity with modern AI architectures and foundation models. Organizational and social
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of Civil and Environmental Engineering (CEE) at the National University of Singapore (NUS) is recruiting a post-doctorate Research Fellow. The successful candidate will work on developing Bayesian networks
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-on experience in infectious disease modeling and vaccinology in an applied government setting while learning and practicing Bayesian methods for nowcasting, forecasting, and Rt estimation. You will also develop
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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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are essential, along with the ability to build and extend statistical pipelines. An interest in Bayesian inference applied to biology is also important. A background in computational proteomics or LC-MS/MS