Research Assistant in Artificial Intelligence
Singapore University of Technology and Design
Singapore

Research Assistant in Artificial Intelligence

Apply now Job no: 494870
Work type: Contract, full-time
Location: Singapore
Categories: Bachelor Degree, Temasek Laboratory, Others

We are seeking a highly motivated research assistant to help with research concerning the computational cost reduction of deep learning models, for object recognition tasks on multi-modal sensor data. The successful candidate will work closely with other team members, and should expect to help with the implementation of reduced-cost deep learning models on robotic prototypes. An ideal candidate would be experienced in both algorithm design and in real-time processing of image/video data.

The goal of the project is to develop vision-based algorithms with low computational cost, for detecting and tracking people. There will be opportunities to work with actual hardware (cameras mounted on robots). The focus is on (significantly) reducing the computational cost while still maintaining a decent performance.

Duration of position: 1 year.

  • Required: Bachelor degree in computer science, mathematics, or data science intensive field.
  • Candidates with Masters degree are welcome to apply as well. Salary package will be based on both academic qualifications and relevant prior work experience.
  • The candidate must have strong understanding of algorithms, and must have strong programming experience in Python.
  • The candidate must have experience in deep learning.
  • Experience with LIDAR and camera data is a huge bonus, but not required.

Interested candidates should submit a current CV and copies of academic transcripts from both post-graduate (if any) and undergraduate studies, directly to Ernest Chong (ernest_chong@sutd.edu.sg) with the email subject header "AI Research Assistant position for reduced-cost deep learning". We regret to inform that only shortlisted candidates will be notified.

Applications close: 30 Nov 2021 Singapore Standard Time


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