Research Fellow (Urban Intelligence Integration Framework for CityScan Phase 2)

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The National University of Singapore invites applications for a Research Fellow to advance urban analytics through an urban intelligence framework. The role spans developing novel algorithms, building robust software, and publishing in top conferences and journals.

Applicants should hold a PhD in Computer Science with AI/ML focus, possess independent research capability, and demonstrate strong programming and communication skills in English.

Qualifications

• PhD in Computer Science with urban intelligence, ML, data mining or AI focus.
• Proven ability to conduct independent research with strong publication record.
• Experience with ML frameworks (PyTorch, TensorFlow) and Python programming.

Responsibilities

• Develop new concepts and algorithms for urban intelligence integration.
• Operate in a fast-paced research environment and deliver results.
• Stay up to date with state-of-the-art methodologies and disseminate findings.
• Translate research into practical tools and workflows through collaboration.
• Contribute to knowledge exchange with external partners and collaborators.

Skills

Python

ML frameworks

English communication

Education

PhD in Computer Science

Tools

PyTorch

TensorFlow

Job description

Company description:

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job description:

Overview

We are looking to recruit a Research Fellow for the project "Urban Intelligence Integration Framework (UI²F) for CityScan Phase 2", which will be hosted at the Institute of Data Science (IDS), National University of Singapore (NUS) and led by Prof Ng See Kiong. This project aims to advance urban analytics methodology through a novel urban intelligence integration framework.

Job Description

Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on a novel urban intelligence integration framework with Foundational Multi-Scale Data Processing, Temporal Relationship Intelligence, and Intelligent LLM-Powered Social Simulation and Decision Support capabilities, that leads to publications in top-tier international conferences and journals, as well as real-world implementations. The role includes designing novel algorithms, building robust software systems, and collaborating with stakeholders to translate research into practical tools and workflows.

Responsibilities:

• Develop new concepts and algorithms in data science, machine learning, and artificial intelligence for urban intelligence integration.
• Ability to work in a face-paced research environment.
• Be up to date on state-of-the-art methodologies in related technical fields and application domains.
• Develop ideas for application of research outcomes.
• Contribute to knowledge exchange activities with external partners and collaborators.

Requirements

• PhD in Computer Science, with specialization related to urban intelligence integration, machine learning, data mining or artificial intelligence.
• Proven ability to conduct independent research with a strong and relevant publication record.
• Prior AI expertise with a strong publication track record in areas such as machine learning, deep learning, reinforcement learning or LLMs/agents.
• Knowledge and demonstrable interest in urban planning with geospatial and temporal data
• Proficiency in programming and software engineering (Python preferred), including experience with ML frameworks (e.g., PyTorch, TensorFlow).
• Excellent interpersonal communication and oral presentation skills in English.