Research Fellow (Information Theory, Statistical Signal Processing, and Machine Learning)
- Recruiter
- NATIONAL UNIVERSITY OF SINGAPORE
- Location
- Singapore
- Posted
- 07 Jun 2023
- End of advertisement period
- 06 Jul 2023
- Ref
- 16044944
- Academic Discipline
- Engineering & Technology, Computer Science, Electrical & Electronic Engineering, Physical Sciences, Mathematics & Statistics
- Job Type
- Academic Posts, Research Fellowships
- Contract Type
- Fixed Term
- Hours
- Full Time
Job Description
The National University of Singapore (NUS) is offering position for postdoctoral fellow who will work closely with Dr. Vincent Tan at the intersection of information theory, statistical signal processing, and machine learning.
Some sample topics include:
- Shannon Theory;
- Multi-Armed Bandits;
- Matrix Factorization and Dictionary Learning;
- Graphical Models
Each position is expected to last from one to two years. The start date is negotiable. The candidate is expected to have a PhD in electrical engineering, computer science, or applied mathematics and a strong publication record in information theory, signal processing, or machine learning.
The candidate will work closely with Dr. Vincent Tan and will use the postdoctoral stint to develop a strong research profile that will enable him/her to find a good faculty position after the postdoctoral stint.
For more information about Vincent Tan's research interests, please visit https://vyftan.github.io/.
Salary will be extremely competitive and will be commensurate with the candidate abilities, potential, and track record.
Applicants should submit a detailed CV to Vincent Tan at vtan@nus.edu.sg. If shortlisted, applicants should also arrange for at least two to three letters of reference to be sent to the same address.
Qualifications
- PhD in Electrical Engineering, Computer Science, or Applied Mathematics
- Open to Fixed Term Contract
More Information
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : Electrical and Computer Engineering
Employee Referral Eligible: No
Job requisition ID : 20782