Research Engineer, SCIS
- Employer
- SINGAPORE MANAGEMENT UNIVERSITY
- Location
- Singapore
- Closing date
- 21 Feb 2021
View more
- Academic Discipline
- Computer Science, Engineering & Technology
- Job Type
- Research Related, Other Research Related
- Contract Type
- Fixed Term
- Hours
- Full Time
- Contract
- Manager
- Bachelor Degree
- Singapore | Closing On 21 Feb 2021
1 year contract or contract till 31 March 2022
About Us
Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together – building a strong collegiality and morale within the university.
Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities – all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.
Job Description
- Problem formulation
- Algorithm development (reinforcement learning and/or imitation learning with sparsity-constraints)
- Conducting experiments using some publicly available datasets
- Paper writing
- Conference presentation
Qualifications
- Minimum Bachelor’s in Computer Science, Information Technology, Information Systems or closely related disciplines
- Minimum 1 year of relevant research experience in reinforcement learning or inverse reinforcement learning
- Proficiency in programming software/languages such as Python/Matlab is required
- Demonstrated experience on (deep) reinforcement learning or inverse reinforcement learning
- Experience with at least one deep learning platform such as Tensorflow is preferred
- Good analytical, technical and problem solving skills
- Applicants with research publications in (inverse) reinforcement learning area will be advantageous
- Self-motivated individual who can work independently and also collaboratively with team members
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