Research Fellow (Computer Science) - Geylang

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 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

Department : Department of Computer Science