Research Fellow: Bayesian inverse problems, high-dimensional Monte-Carlo methods and Data Assimilation, Bayesian Deep Learning Salary Range: S$70K -- S$85K Department of Statistics and Applied Probability, NUS, Singapore
The department of Statistics and Applied Probability of the National University of Singapore has a postdoctoral position available. Topics of interest include, but are not limited to: PDE constrained Bayesian inverse problems, high-dimensional Monte-Carlo methods (MCMC, particle methods, optimal transport), high-dimensional Data Assimilation (SMC, EnKF, Variational approaches, Hybrid Methods), Bayesian Deep Learning models for inference in data-scarce settings. These project are in collaboration with (i) Abyss Processing, a young and energetic startup specializing in leveraging Deep Learning for medical diagnosis (ii) the Solar Energy Research Institute of Singapore (SERIS). The candidate will work closely with Dr. Alex Thiery and will use this postdoctoral stint to develop a strong research profile that will enable him/her to find a good faculty position. Applicants should be highly motivated and creative, show an exceptional track record, and hold a Ph.D. degree in Computational Statistics, Computer Science, Signal Processing, Mathematics, or related fields, and be interested in working in an interdisciplinary and multicultural environment. Positions for postdocs who just obtained their Ph.D. degree and for experienced researchers with several years of postdoctoral experience are available. These positions offer the opportunity to gain leadership and supervision experience in joint projects with younger scientists. Term of Appointment: the appointment can commence immediately. Interested candidates are encouraged to directly contact Dr. Alex Thiery (a.h.thiery "@" nus.edu.sg<http://nus.edu.sg>) for further details -- http://bit.ly/2KXDYyI ________________________________ Important: This email is confidential and may be privileged. If you are not the intended recipient, please delete it and notify us immediately; you should not copy or use it for any purpose, nor disclose its contents to any other person. Thank you.
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