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will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies
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Scalable Inference: Develop new algorithms for scalable uncertainty quantification (UQ) and Bayesian inference and apply them to challenging simulation problems. The goal is to produce robust, validated
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of biofouling processes in marine environments. This role will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how
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demonstrated publication record in peer-reviewed scientific journals, particularly in avian population ecology Excellent statistical skills, including experience writing Bayesian hierarchical population models
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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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knowledge of key AI methods such as deep learning, operator learning, and Bayesian optimization, and apply it to develop next-generation surrogate models. This position will enable you to coordinate and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 27 days ago
to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig economies and prediction markets. Opportunity to supervise research students and work as part of a
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create new mathematical approaches, algorithms and software to advance scientific research in multiple disciplines, often in collaboration with other Flatiron Centers. CCM has particularly strong research
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/Seurat, count models, batch correction, differential analyses). Strong grounding in statistics (GLMs, hierarchical/Bayesian modeling, multiple testing) and experimental-design principles. Bioinformatics
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-GRASP”, “Simulation-Based Bayesian Inference for Object Perception in Robot Grasping”, financed by the European Union´s Horizon Europe research & innovation programme under the euROBIN project (Grant