Research Associate: Neuromorphic AI & Continuous-Time

ntu; Singapore; Sur place; SGD 39 000 - 56 000; Plein temps

Résumé du poste

NTU Singapore, a leading research university, invites applications for a position within the College of Computing and Data Science. The role focuses on designing efficient continuous-time models for neuromorphic sensors and evaluating their scalability, with applications in embodied AI.

Candidates should hold a Master degree in relevant fields, demonstrate strong analytical and collaborative skills, and show capacity to conduct innovative research. Flexible hours may be required.

Qualifications

• Master degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent.
• 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.
• Ability and willingness to work some flexible hours.

Responsabilités

• Design efficient continuous-time models for neuromorphic sensors
• Study scalability of the designed continuous-time models
• Apply the designed models for embodied AI applications

Connaissances

Independent

Analytical thinking

Teamwork

Communication skills

Research capability

Proactive

Formation

Master degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent

Description du poste

NTU Singapore, a leading research university, invites applications for a position within the College of Computing and Data Science. The role focuses on designing efficient continuous-time models for neuromorphic sensors and evaluating their scalability, with applications in embodied AI.

Candidates should hold a Master degree in relevant fields, demonstrate strong analytical and collaborative skills, and show capacity to conduct innovative research. Flexible hours may be required.