Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
25 Nov 2025 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
-
Singapore Application Deadline 10 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
well as academic guidance and mentorship. The scholarship may be awarded to applicants who have just completed their undergraduate studies; or have completed a Bachelor’s degree or a Master’s programme and/or have
-
(R1) Country Singapore Application Deadline 17 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
(R1) Country Singapore Application Deadline 16 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
Researcher (R1) Country Singapore Application Deadline 25 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
-
supervisor. Job Requirements: Bachelor’s degree or above in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or related fields. Hands-on experience with deep learning frameworks such as
-
of novel federated causal inference algorithms and associated software APIs. Validation of algorithms via simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer
-
Singapore Application Deadline 14 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
. Ubuntu) Experience with version control systems (e.g., Git or CVS). Knowledge and some practical experience in areas such as Reinforcement Learning (RL), imitation learning, motion planning, computer