Research Scientist (CFAR), IHPC

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 80,000 - 110,000; Full time

Job summary

A leading research institute in Singapore is seeking a Research Scientist to advance the development of AI technologies in maritime applications. You will optimize machine learning frameworks for sub-group specific alignment of large language models and collaborate with diverse research teams. The ideal candidate holds a PhD in related fields and has expertise in AI, reinforcement learning, and maritime informatics. This role offers a chance to contribute to cutting-edge research in a dynamic environment.

Qualifications

• Strong background in AI, reinforcement learning, and deep learning.
• Solid foundation in mathematics and ability for theoretical proofs.
• Experience with LLM alignment techniques.

Responsibilities

• Develop alignment frameworks for sub-group value-sensitive representations.
• Design parameter-efficient fine-tuning techniques within LLM alignment.
• Build machine learning pipelines to optimize port operations.

Skills

AI

Reinforcement Learning

Deep Learning

Mathematics

Maritime Informatics

Education

PhD in Computer Science or related fields

Job description

A*STAR Centre for Frontier AI Research (A*STAR CFAR) is seeking an innovative Research Scientist to contribute to the development of cutting-edge AI technologies in maritime applications, value alignment, and resource-efficient large language model (LLM) adaptation. This role focuses on advancing alignment techniques for large language models (LLMs), enabling fine-grained, sub-group specific alignment deployable on personal devices. The candidate will also work on developing and applying machine learning techniques to solve practical challenges in vessel route prediction, port operations optimization, and global trade flow analysis.

ABOUT A*STAR AND CFAR

At A*STAR, we make it our mission to attract and develop a diversity of talent along the research, innovation, and enterprise value chain, with career paths developed for scientists, engineers, and entrepreneurs. In return, we commit to investing in the personal and professional growth of each of our officers.

CFAR has a team of exemplary AI researchers committed to solve most exciting problems in the future AI, including IEEE fellows, chairs, scholars, and advisors among some of the most highly cited researchers in the world. Our AI Centre provides a unique research environment for fundamental AI research and cultivate next-gen AI scientists. If you are passionate about advancing AI alignment in multicultural societies and enabling scalable, efficient LLM adaptation, we encourage you to apply.

Successful candidates will be responsible, but not limited to:

• Develop alignment frameworks to create social value-sensitive representations for sub-groups and to enable inference-time output refinement aligned with sub-group values.
• Design and implement parameter-efficient fine-tuning techniques within the LLM alignment context.
• Develop models for trajectory prediction and route reconstruction of ocean-going vessels using AIS data, satellite imagery, and contextual information.
• Build machine learning pipelines to optimize port operations, including vessel arrival forecasting, berthing planning, and congestion mitigation.
• Collaborate with interdisciplinary teams to integrate domain knowledge from linguistics, social sciences, and maritime technology.

JOB REQUIREMENT

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields.
• Strong background in AI, reinforcement learning, and deep learning, with expertise in areas such as generative models, agent learning, or spatio-temporal modeling.
• Solid foundation in mathematics, capable of independent theoretical proofs, algorithm design, and integration with machine learning, optimization, and statistical modeling.
• Experience with Maritime Informatics and LLM alignment techniques, such as Reinforcement Learning with Human Feedback (RLHF).
• Proficiency in developing efficient AI models, including parameter-efficient fine-tuning or inference-time adaptation methods.
• Strong publication records in prestigious conferences and journals, such as TPAMI, NeurIPS, ICML, ICLR, AAAI, IJCAI, JR, TKDE, AI.
• Ability to work independently and collaboratively within interdisciplinary research teams.