Research Assistant: Interpretable AI for Dynamical Systems

National University of Singapore; Singapore; On-site; SGD 40,000 - 60,000; Full time

Job summary

The National University of Singapore is seeking a Research Assistant (XAI) to enhance mathematical foundations of interpretable algorithms in the field of dynamical systems.

The candidate will work on developing novel modeling methods with applications in Earth system science, focusing on explainable AI solutions. Qualifications include expertise in machine learning and dynamical systems algorithms.

Qualifications

• Experience in machine learning applications.
• Knowledge in explainable AI models.
• Familiarity with algorithms for dynamical systems.

Responsibilities

• Advance the foundations of interpretable algorithms for dynamical systems.
• Develop methods for modeling and simulating complex dynamical processes.
• Focus on connections to physics-informed learning and interpretable machine intelligence.

Skills

Machine learning

Explainable AI

Algorithms for simulation of dynamical systems

Signal processing

Job description

Job Title: Research Assistant (XAI)

University-Level Unit: College of Design and Engineering

Faculty/Department-Level Unit: Mechanical Engineering

Employee Category: Research Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 25/06/2026

Job Description

This position focuses on advancing the mathematical and computational foundations of interpretable algorithms for dynamical systems and explainable AI. The successful candidate will develop new methods for modelling, simulating, and understanding complex dynamical processes with a focus on Earth system science, and connections to physics-informed learning, and interpretable machine intelligence.

Qualifications

• Machine learning
• Explainable AI
• Algorithms for the simulation of classical dynamical systems (including climate-relevant targets such as transport, multiscale flows, and extremes)
• Signal processing, time evolution, and structure-preserving transformations
  
  

Req ID: 33520