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Field
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modeling and analysis. Ability to select, implement, diagnose, and adapt parameter-estimation or statistical-inference methods to suit the model, data structure, and scientific question. Experience with
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The Statistics (STAT) program in the Computer, Electrical, and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa ) at King Abdullah University of Science and Technology
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spatial meteorological data. Models GPS location data of animals to estimate movement behavior. Develops statistical models (especially Bayesian hierarchical models) of wildlife disease surveillance data
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limited to mathematical statistics, probability theory, computational statistics, Bayesian modeling, zero-inflated ecological models, spatio-temporal modeling, probabilistic sampling, hierarchical modeling
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Computer Science, Robotics, Systems Engineering, Electrical and Computer Engineering, Mechanical Engineering, Chemical Engineering, Materials Science & Engineering, Chemistry, or a related quantitative scientific
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Responsibilities • Develop and extend Bayesian semi-mechanistic renewal equation models for estimating genotype-specific reproduction numbers and immune escape. • Build scalable inference pipelines integrating
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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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-time, and evidence-accumulation phenomena. Implement simulation, parameter-estimation, and model-comparison methods in Python, MATLAB, R, or related computational environments. Lead and co-author
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research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs
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and climate adaptation worldwide. Your research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build