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About the Role The Centre for Epidemic Response & Modelling (CERM) at NUS Saw Swee Hock School of Public Health seeks a Research Fellow with deep expertise in Bayesian statistical modelling and
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for Bayesian inference, inverse problems, uncertainty quantification, and scientific machine learning, with applications in environmental, scientific, and industrial imaging. The role/Te mahi We invite
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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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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or a closely related discipline. Knowledge of genetics and genomics and a passion for applying quantitative approaches to biological and medical research questions. Strong expertise in (Bayesian
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trials, multiple endpoints, adaptive designs, Bayesian design and analysis methods, estimands, meta-analyses, benefit-risk analyses, subgroup analyses, biosimilars, patient experience data, bioequivalence
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in mathematical modelling and Bayesian inference while learning from three collaborating chief investigators. You will also build your publication record and professional networks through seminars
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-noise amplifiers, filters, ADCs, sensor biasing and excitation). Experience in developing medical devices or wearable/implantable sensing systems, and awareness of relevant standards and regulations (e.g
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system level simulation studies • Propose and innovate solutions for operational challenges in hardware such as common mode noise, electromagnetic interference, filter design, etc for better motor and
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statistical modelling, particularly Bayesian and/or hierarchical models A track record of scientific writing, demonstrated through theses, manuscripts, reports, publications, or other research outputs