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such as Bayesian modelling and optimal control theory. Using state-of-the-art methods – including virtual reality, wearable sensing, motion platforms and advanced data analytics – you will place particular
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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Bayesian meta-analyses. This position also provides opportunities to develop innovative statistical methods related to clinical trial design, variable selection in high-dimensional data, prediction
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Previous Job Job Title Post-Doctoral Associate - Measurement and Manipulation of Developing Cortical Networks Next Job Apply for Job Job ID 370353 Location Twin Cities Job Family Academic Full/Part
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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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Classification Title: Postdoctoral Position – Neuroimaging - Developmental Network Neurobiology Laboratory Job Description: The University of Florida, Department of Pediatrics, Neuroimaging
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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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understanding of data quality, reproducibility and robust analytical practice. Experience of SQL, cloud-based or high-performance computing environments, and Bayesian methods would also be valuable. Beyond
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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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diverse set of time-dependent forecasting models (e.g., neural network, mechanistic, statistical, and data-driven) to serve as experts within the integrative architecture. (iii) Mixture-of-experts