Research Fellow (Computer Science)

National University of Singapore; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

The National University of Singapore is seeking a Research Fellow for a project on multimodal time-series analytics. The role involves advanced research in explainable AI and requires a PhD in a relevant field, along with strong technical and communication skills. Successful applicants will contribute significantly to a pioneering educational initiative.

Qualifications

• PhD obtained within the last five years.
• Strong publication record in reputable conferences.
• Research experience in time-series analytics or natural language processing.

Responsibilities

• Conduct research on multimodal learning and explainable AI.
• Lead technical development efforts within the project.
• Mentor graduate and undergraduate students.

Skills

Proficiency in Python

Deep learning frameworks

Natural language processing

Multimodal learning

Explainable AI

Communication skills

Education

PhD Degree in Computer Science, Artificial Intelligence, or related field

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:

Job Description

Research Fellow - Multimodal Time-Series Analytics & Explainability development of algorithm and system for the project

The School of Computing at the National University of Singapore (NUS) invites applications for a Postdoctoral Research Fellow position in the area of time-series analytics and explainable AI. The successful candidate will contribute to the MOE-funded project "Time Will Tell (TwT)", which explores natural language-based interaction with time-series data. The role involves conducting research on multimodal learning and leading technical development efforts within the project.

Qualifications

Applicants should meet the following requirements:

• PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year
  
  
• Research Experience in one or more of the following areas:
  • Time-series analytics or forecasting
  • Natural language processing (especially question answering or language grounding)
  • Multimodal learning (e.g., combining text with temporal or numerical data)
  • Explainable AI (XAI) or interpretable machine learning
    
    
• Strong Publication Record in reputable international conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGMOD, VLDB)
  
  
• Technical Skills:
  • Proficiency in Python and major deep learning frameworks such as PyTorch or TensorFlow
  • Familiarity with transformer architectures and large language models (e.g., BERT, GPT)
  • Experience in building, training, and evaluating deep learning models on real-world datasets
    
    
• Communication & Collaboration:
  • Ability to work independently and as part of a collaborative research team
  • Strong written and oral communication skills
  • Commitment to mentoring graduate and undergraduate students
    
    
• Desirable (but not required):
  • Experience with time-series QA datasets (e.g., Time-MQA, TSQA, MTBench)
  • Background in signal processing or domain-specific time-series (e.g., financial, medical)
  • Experience with open-source contributions or system/toolkit development

More Information

Location: Kent Ridge Campus

Organization: School of Computing

Department : Department of Computer Science