Research Associate (Computer Vision)
The successful candidates will contribute to research activities related to developing computer vision systems to improve construction site safety. The candidates shall work under the supervision of the Principal Investigator (PI) to conduct academic research and/ or administrative work. Specific job activities may include:
- Design and conduct research studies related to computer vision and machine learning;
- Conduct literature review on appropriate topics related to the project; and
- Write research papers, reports and proposals.
Within the fields of machine learning, computing, construction and facilities management, engineering or related field
- Master of Science or Engineering with at least 2 years’ relevant work experience, and good knowledge, skills and expertise in relevant field;
- Knows Python, PyTorch, and Tensorflow;
- Willing to learn, independent and responsible; and
- Strong writing and communication skills.
Candidates with the following will be preferred (not compulsory):
- Prior experience with computer vision developments, such as image classification, object detection and segmentation;
- Publications in peer-reviewed journals;
- Work experience in facilities management, construction or other heavy industry.
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.
Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department : The Built Environment
Employee Referral Eligible: No
Job requisition ID : 17262