Full Time Research Fellow (Computer Vision - Multimodal Deep Learning) Jobs, in Nanyang Technological University Southwest (Singapore) - Maukerja

Hyundai-NTU-A*STAR Corporate Lab offers an excellent R&D environment to create novel technologies with the world leading automotive company, Hyundai by translating the research into the dark factory directly with implementing and validating the research using AI, Robotics, 3D Printing and Digital Twins.

We are looking for a research fellow to work on computer vision and deep learning techniques for the task of object detection under challenging scenarios. The role will focus on multimodal detection models, accurate and efficient detection models under various data constraints.

Key Responsibilities:

• The candidate will research and develop a methodology/framework for multimodal large language models.
• The candidate will research and develop a methodology/framework for multimodal object detection.
• The candidate is required to report its research findings in the form of a report and/or present its research findings in international peer-reviewed conferences/journals.
The candidate is to be involved in the mentoring of Masters/FYP students

Job Requirements:

• PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent.
• Good R&D experience in multimodal large language models
• Independent, highly analytical, proactive and a team player
• Excellent teamwork and verbal, written communication skills
• In-depth knowledge relevant to the project domain.
• Demonstrated capability to conduct innovative research.
• The ability and willingness to adapt and incorporate novel ideas and approaches in scientific industry.
• Demonstrated ability to formulate hypothesis and design effective experimental plans.
• Ability to design and implement new experimental methods.
• High-level expertise in the required experiment or modelling methods.
• Ability to initiate collaboration research in multidisciplinary team.
Oversee and report project progress.

We regret to inform that only shortlisted candidates will be notified.