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The postdoctoral fellow will work on problems at the intersection of information theory, statistical signal processing, and machine learning, with topics potentially including the following:
- Algorithms and theory for high-dimensional inference and learning (e.g., graph learning, structured estimation)
- Sequential decision-making algorithms under uncertainty (e.g., black-box optimization, bandits, ranking)
- Information-theoretic limits for problems in statistical inference, learning, and optimization
- Machine learning methods applied to communication and signal processing problems
Further information on Jonathan Scarlett's research interests can be found at https://www.comp.nus.edu.sg/~scarlett/.
The position is expected to last for at least 1 to 2 years. The candidate should have a PhD in a relevant area such as information theory, statistical signal processing, machine learning, or theoretical computer science, and a strong publication record.
The salary will be very competitive, and commensurate with the candidate's abilities and track record.
Applicants should submit a detailed CV and a short statement of research interests to Jonathan at email@example.com. Shortlisted applicants will later be asked to arrange for at least two reference letters to be sent to the same address.