Research Assistant (Full-Stack Development)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link https://careers.nus.edu.sg/job/Research-Assistant-%28Full-Stack-Development%29/32474-en_GB/ We regret that only shortlisted candidates will be notified. Position Overview A/P Chen Ying from Mathematics Department, National University of Singapore is seeking a highly motivated and technically proficient Research Assistant (Full-Time) to lead the end-to-end design and development of interactive systems for cutting-edge optimization and machine learning (ML) models. This role is pivotal in "translating" complex academic research into functional, high-fidelity web applications and interfaces. You will work at the intersection of applied software engineering, user-centered design, and AI systems. Major Responsibilities • Full-Stack Development: Lead the design and implementation of intuitive UIs and robust backend architectures for ML models. • System Integration: Build and maintain data collection pipelines and experimental setups that bridge backend mathematical models with frontend interfaces. • Architecture & Scaling: Maintain clean, scalable codebases and assist in the deployment of research tools to cloud or edge environments. • Rapid Prototyping: Develop high-fidelity UI prototypes through iterative, user-centered design cycles. • Collaboration: Actively participate in lab meetings and workshops with professors, research fellows, and industry partners. Qualifications • Bachelor’s degree in Computer Science, Software Engineering, Engineering or a related technical field • Strong experience with modern web frameworks, with a preference for React.js. • Proficiency in Python and experience with backend frameworks such as FastAPI, Flask, or Django. • Familiarity with relational databases (e.g., PostgreSQL, MySQL) or NoSQL solutions (e.g., MongoDB). • Proficiency in version control (Git) and modern development environments (VS Code, PyCharm, etc.). • Ability to explain technical trade-offs to a multidisciplinary team. Preferred (Bonus) Skills • Experience in designing and consuming APIs Design. • Experience with human-centered design • Exposure to machine learning pipelines (Scikit-learn, PyTorch, or TensorFlow) and model deployment. • Experience with containerization (Docker) and cloud services (AWS, Firebase, or similar).