Research Assistant, AI (School of Computing)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant%2C-AI-%28School-of-Computing%29/32842-en_GB/st=C1F8DE6EC5F404637EBF67E5324B49A6BA0AC38B

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking highly motivated and skilled researchers to drive innovation in trustworthy AI. The ideal candidate should possess expertise in one or more of the following research areas:
. Model Robustness and Safety: fairness, value alignment, adversarial robustness, model jailbreaking, etc.
. Cognitive capabilities: reasoning model, mitigating model hallucination, symbolic knowledge machine learning, etc.
. Multilingual and multicultural foundation models

The successful candidate will work on advanced techniques across various data modalities, including textual, visual, and auditory data.

You will be expected to:
. Collaborate with a diverse team of computer scientists and domain experts to contribute to an interdisciplinary research programme.
. Conduct rigorous research and develop innovative solutions to complex problems.
. Publish and present research findings in academic journals and conferences.
. Develop and present demos for your research.
. Assist in the development and testing of algorithms or behavioral models.
. Participate in regular team meetings and contribute to collaborative efforts.

Key Responsibilities:
. Investigated the ethical and technical boundaries of AI safety, providing critical insights for new research directions.
. Develop state-of-the-art methods for improving the trustworthiness of multimodal models.
. Collaborate with a multidisciplinary team of researchers, data scientists, and engineers.
. Publish research findings in top-tier conferences and journals.

Qualifications

Qualifications:

• A bachelor's degree in computer science/computer engineering.
• The candidate's track record in publication and strengths as an independent researcher are valued.
• Strong experience in machine learning and deep learning.
• Excellent programming skills in Python, TensorFlow, PyTorch, or similar frameworks.
• Proficiency in handling multimodal data, including text, images, audio, and video.
• Good written and verbal communication skills in English
• Prior publications in major machine learning (NeurIPS/ICML/ICLR), computer vision (CVPR/ICCV/ECCV), or multimedia (ACM Multimedia) conferences is a plus

Preferred Qualifications:

• Prior experience in interdisciplinary research.
• Interest in the impact of digital technologies and AI safety on society.