Research Fellow, School Of Computing

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow%2C-School-of-Computing/33609-en_GB/?st=9C609F31A7211FCD57928535B52041204BFBE780 We regret that only shortlisted candidates will be notified. Job Description The National University of Singapore invites applications for the position of Research Fellow in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights, developing novel computational solutions to a wide range of applications, building large-scale experimental systems and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems. We are looking for Research Fellow in the area of Automatic Programming. This position will be part of a Singapore Ministry of Education (MoE) Tier 3, multi-year research program named "Automated Program Repair" which has been funded 2022-2027. This is a large research program involving several research projects in analysis, verification, test generation and applications related to program repair. To see work done on program repair at NUS, kindly see the webpage https://nus-apr.github.io/ The work will involve assured autonomy in software engineering by building on the recent success of the group in building AutoCodeRover, see https://arxiv.org/abs/2404.05427 https://x.com/AbhikRoychoudh1/status/177749400 0611852515?mx=2. Qualifications Ph.D. in Computer Science or a closely related field. Has prior research experience in machine learning and static methods for program repair Excellent research skills, including data analysis, interpretation, and scientific writing. Strong communication and collaboration skills. Ability to work independently and manage multiple tasks effectively. Only shortlisted candidates will be notified.