Research Engineer, Machine Learning
- NATIONAL UNIVERSITY OF SINGAPORE
- 01 Mar 2023
- End of advertisement period
- 31 Mar 2023
- Academic Discipline
- Engineering & Technology, Computer Science, Physical Sciences, Mathematics & Statistics
- Job Type
- Research Related, Other Research Related
- Contract Type
- Full Time
Vessel Collision Avoidance System is a real-time framework to predict and prevent vessel collisions based on historical movement of vessels in heavy traffic regions such as Singapore strait. We are looking for talented developers to join our development team to help us develop machine learning and agent-based simulation models to quantify vessel collision risk at Singapore strait and port. If you are data curious, excited about deriving insights from data, and motivated by solving a real-world problem, we want to hear from you.
A B.Sc. in a quantitative field (e.g., Computer Science, Statistics, Engineering, Science) Good coding habit in Python and able to solve problems in a fast pace Familiar with popular machine learning models Eager to learn new things and has passion in work Take responsibility, team oriented, and result oriented The ability to communicate results clearly and a focus on driving impact
Covid 19 Message
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
Department : Industrial Systems Engineering And Management
Employee Referral Eligible: No
Job requisition ID : 7334