Research Associate (Faculty of Law -TRAIL)

NATIONAL UNIVERSITY OF SINGAPORE; Pasir Panjang; On-site; MYR 100,000 - 150,000; Full time

Job summary

A leading university in Southeast Asia is inviting applications for a Research Associate position focused on artificial intelligence and law. You will be responsible for researching and collaborating on projects involving machine learning and LLMs. Candidates should have a degree in Computer Science and experience in a relevant field, as well as proficiency in Python. The role offers competitive remuneration and opportunities for research funding and academic collaboration.

Benefits

Competitive remuneration package

Opportunity for research funding

Access to state-of-the-art resources

Qualifications

• Strong knowledge of statistics, machine learning, and optimization.
• Good to excellent command of English; additional languages appreciated.
• Familiarity with LLM architectures and evaluation methods.

Responsibilities

• Conduct research for foundational LLM projects.
• Collect and normalize datasets for training LLMs.
• Collaborate with interdisciplinary teams.

Skills

Machine Learning

Statistics

Database Management

Python

Interpersonal Communication

Education

Bachelor's or Master's in Computer Science

Master's degree with 2 years' experience

Tools

PyTorch

Regex

C++

JavaScript

Job description

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The Centre for Technology, Robotics, Artificial Intelligence and the Law (TRAIL) was launched on 5 December 2019. Its focus is to inform the debate on the legal, ethical, policy, philosophical and regulatory questions associated with the use and development of information technology (IT), artificial intelligence (AI), data analytics and robotics, in the context of the Fourth Industrial Revolution, through contributions by way of original thinking, research, writing and publications; and to collaborate with like-minded research centres around the world to further inter-disciplinary research in, and the development of, possible guidelines, standards, and solutions to the legal, ethical, policy, philosophical and regulatory issues associated with the development and application of IT, AI, data analytics and robotics in key industries.

BENEFITS

1. An opportunity to address cutting-edge legal issues through the application of machine learning research and to collaborate with leading experts in Singapore and internationally.
2. One-year contract position, with the possibility of renewal based on performance and funding availability.
3. Competitive remuneration package, commensurate with qualifications and experience.
4. Eligibility to apply for TRAIL research and conference funding to support attendance at academic conferences and pursue independent research under the supervision of the Principal Investigator.
5. Dedicated workstation and access to TRAIL facilities and resources.

DUTIES

Reporting to the Principal Investigator, you will play a key role in research initiatives involving foundational LLMs. Your responsibilities include:
• Conducting research for and collaborating on funded research projects involving foundational LLMs, including identifying, evaluating, and developing relevant technologies and resources.
• Collecting, normalising, and creating datasets, as well as training LLMs.
• Analysing and interpreting LLM results, evaluating model performance and recommending methods for improvement.
• Collaborating with legal and computing researchers on interdisciplinary projects.

You are expected to be in residence for the duration of your appointment, in line with standard NUS annual leave provisions. Flexible or remote work arrangements may be considered, provided baseline on-site work requirements are met to ensure effective collaboration and team cohesion.

REQUIREMENTS

REQUIREMENTS

• Bachelors or Masters in Computer Science, Machine Learning, Artificial Intelligence or Computational Linguistics, with a strong knowledge of statistics, machine learning and optimisation.
• Good to excellent command of English (oral and written), with additional language proficiency being an advantage.
• Familiarity with modern LLM architectures (transformer encoder, decoder and encoder-decoder models).
• Experience handling large datasets, with strong structured and unstructured database management skills.
• Knowledge of LLM evaluation methods, metrics, inference processes and deployment setups.
• Proficiency in Python, with additional skills in Regex, C++ and JavaScript a bonus.
• Proficiency with Python-based neural network frameworks, especially PyTorch, and training LLMs on parallelised Nvidia architectures.
• Strong interpersonal and communication skills, with the ability to work collaboratively in a team.
• Self-motivated, organised, detail-oriented and be able to work independently to meet deadlines.

Research Associate
An appointment as a Research Associate may be offered to an applicant who has a Master’s degree and/or a further minimum of two years’ post-graduation experience.

APPLICATION PROCEDURE

Interested applicants are invited to apply and submit their applications directly at our NUS Career Portal. These must comprise:

1. Covering Letter
This should, inter alia, explain the reason(s) for your interest in the position.

2. Curriculum Vitae
A curriculum vitae should be submitted containing complete and detailed information on your academic institutions, honours, awards, all publications to date, and all academic, research and professional experience (current and previous, including dates of employment and job descriptions).

3. Submission of Application Materials
Interested applicants are invited to apply and submit their applications directly from NUS Career portal.

4. Closing Date
The closing date for the receipt of applications and references is Monday, 20 October 2025. Late applications cannot be considered.

5. Shortlisting and Interview
Only shortlisted applicants will be contacted concerning the status of their application.