Publisher
source

National University of Singapore

Postdoc in Bayesian Machine Learning for Healthcare at National University of Singapore / Duke-NUS Medical School National University of Singapore in Singapore

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

Singapore

University

National University of Singapore

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Keywords

Computer Science
Mathematics
Mobile Health
Medical Science
Salud Pública
Statistics
Applied Mathematic
Machine learning

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About this position

Postdoctoral Research Scholar opportunity in Bayesian machine learning for healthcare at the National University of Singapore and Duke-NUS Medical School. The position is jointly mentored by Yan Shuo Tan and Bibhas Chakraborty and is funded by an NUS Cross Faculty Grant on personalized healthcare via Bayesian machine learning.

The research focuses on developing machine learning solutions for healthcare problems, including dynamic treatment regimes, mobile health, and trial simulations. Methods mentioned include Prior-Data Fitted Networks (PFNs), Bayesian Additive Regression Trees (BART), and generative methods for tabular data. Day-to-day work includes software development, numerical experimentation, deep learning, theoretical research, academic writing, and collaboration with medical researchers.

Applicants should have a PhD in statistics, computer science, applied mathematics, or a related field, with a strong foundation in statistical and computational principles. The postdoc is a two-year appointment and is open until filled.

The same group page also lists fully-funded PhD positions in statistical machine learning at NUS, with research directions including tree-based methods and ensembles, Bayesian machine learning, interpretability, PFNs, and agentic data science.

How to apply: email the supervisor directly with a CV, brief research statement, a representative publication, and contact details for two references. For the PhD opening, apply through the NUS Department of Statistics and Data Science PhD admissions portal.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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