NATIONAL UNIVERSITY OF SINGAPORE

Tenure Track Faculty, Data Science

3 days left

Location
Singapore
Posted
22 Dec 2021
End of advertisement period
21 Jan 2022
Ref
6553144
Contract Type
Permanent
Hours
Full Time

Job Description

The Institute for Data Science (IDS) at the National University of Singapore (NUS) invites applications for a tenure-track faculty position in inter-disciplinary data science, with expertise in one or more of the following areas:

  • Representation learning
  • Causality in machine learning
  • Continual learning

We seek candidates who are passionate about taking a transdisciplinary approach to advance data science research and its impact, and who are open to collaborating with colleagues from Engineering, Computing, Business, Medicine, Public Health, Arts and Social Science.  Successful candidates will be matched to a host department at NUS based on their primary research interests and expertise, e.g., Department of Computer Science, Department of Electrical and Computer Engineering, Department of Mathematics, or Department of Statistics & Data Science. 

The Institute for Data Science (IDS) is a highly interdisciplinary institute spanning multiple faculties and departments throughout NUS, and offers a unique interdisciplinary PhD program.  Further information can be found at https://ids.nus.edu.sg/.  Faculty members with IDS will have the opportunity to advise PhD students both from the IDS program and from their host department’s program.  Teaching duties will be based in the host department.

Requirements

Candidates should demonstrate excellent research potential, and a strong commitment to teaching. Truly outstanding applicants may also be considered for the prestigious Presidential Young Professorship.

Applicants should send a single .zip file to ids@nus.edu.sg containing the following documents as clearly labelled individual PDF files:

  • A short cover letter mentioning the position and the applicant’s research interests
  • Curriculum Vitae, including a full publication list
  • Research statement
  • Teaching statement
  • Contact information of at least 3 referees that may be contacted if shortlisted

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