Research Fellow in Computer Engineering/Computer Science/Electronics Engineering
Nanyang Technological University Singapore
Singapore · Full Time
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- Salary
- —
- Openings
- 1
- Posted
- 1 week ago
- Work mode
- In office
- Education
- PhD preferred
- Resume
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Job description
About the Institution
Nanyang Technological University (NTU) in Singapore is a dynamic, research-focused university ranked among the world’s top academic institutions. Its College of Computing and Data Science (CCDS) stands out for its cutting-edge curriculum, impactful research, and prestigious faculty. NTU CCDS fosters innovation and leadership in areas such as AI, data science, and computing, making it an inspiring environment for learning and growth.
Primary Responsibilities
- Conduct comprehensive literature reviews on diffusion models, focusing on their application in sampling from un-normalized probability distributions.
- Analyze and summarize recent advances in inference techniques for state-space models using particle filters.
- Develop, implement, and theoretically analyze novel inference methods based on diffusion models.
- Contribute research findings by publishing in prominent international journals and conferences.
- Present research outputs to the global academic community and build professional networks through international conferences.
- Engage actively in departmental activities such as reading groups and seminars.
Candidate Requirements
- PhD or equivalent qualification in Computer Engineering, Computer Science, Electronics Engineering, or a related field is preferred.
- Ability to work independently while being highly analytical and proactive.
- Excellent teamwork skills, complemented by strong verbal and written communication abilities.
- Deep expertise relevant to the research domain.
- Proven track record in conducting innovative research.
- Willingness to incorporate new ideas and approaches from industry and academia.
- Skill in formulating research hypotheses and designing effective experimental plans.
- Capability to create and implement new experimental methods.
- High proficiency in the experimental or modeling techniques necessary for the research.
- Aptitude for initiating collaborative projects within multidisciplinary teams.
- Experience overseeing projects and reporting progress.
- Flexibility to work varied hours as needed.
Additional Information
Only shortlisted candidates will be contacted for further consideration.
Minimum education
Doctorate