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Research Assistant; Online Trust and Safety

Remote / Online - Candidates ideally in
Singapore
Listing for: National University of Singapore
Remote/Work from Home position
Listed on 2026-10-07
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 33000 - 56000 SGD Yearly SGD 33000.00 56000.00 YEAR
Job Description & How to Apply Below
Research Assistant (Online Trust and Safety)

University-Level Unit:
NUS Centre for Trusted Internet & Community Faculty/Department-Level Unit:
NUS Centre for Trusted Internet & Community Employee Category:
Research Staff Location:
Kent Ridge Campus Posted On:
22/09/2026

Introduction

The Department of Communications and New Media (CNM) at the National University of Singapore is seeking a Research Assistant with a background in Computer Science or Data Science to support a project funded by the Online Trust and Safety (OTS) Research Programme. The project develops multilingual corpora, annotation pipelines, and severity detection models for online harm in Singapore's digital spaces.

Job Description

The Research Assistant will contribute to the technical infrastructure of the project across four phases. Phase 1 involves developing automated data collection scripts and tools for extracting content from Singaporean online platforms (Facebook, Instagram, X/Twitter, Reddit) using licensed APIs. Phase 2 involves data cleaning, preprocessing, and corpus management. Phase 3 involves machine learning experiments, including fine-tuning large language models (e.g., Llama 70B) for harmful content annotation and developing multimodal toxicity detection pipelines.

Phase 4 involves tabulation of results, preparation of figures, and contribution to technical reports and papers.

Qualifications
  • Minimum Bachelor's Degree in Computer Science, Data Science, or a closely related field
  • Proficiency in Python and familiarity with NLP libraries (Hugging Face Transformers, spaCy, or equivalent)
  • Experience with large language models, fine-tuning, and/or multimodal machine learning
  • Familiarity with data collection via APIs and web scraping tools
  • Knowledge of statistical analysis and experience working with large unstructured datasets
  • Excellent written and verbal communication skills.

We regret to inform that only shortlisted candidates will be notified.

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