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We are seeking a highly motivated Research Engineer II to join our team at NTU Singapore. As a key member of our project team, you will contribute to the development of novel methodologies for uncertainty quantification in Large Language Models.
About the RoleThis fixed-term position offers the opportunity to work on cutting-edge research projects and collaborate with an interdisciplinary team of experts in AI, Data Science, and Computer Science.
The ideal candidate will have a strong background in computer science, statistics, or a closely related field, with a proven track record of publications in machine learning or related fields.
Key Responsibilities- Set up and maintain the project's compute infrastructure, ensuring that these meet the needs of the project.
- Maintain the project's internal communication infrastructure to facilitate effective collaboration among researchers.
- Contribute to novel methodologies for uncertainty quantification in Large Language Models, including developing new ideas, acting as a source of information and advice, enabling large scale research implementations, managing research experiments, contributing to writing research papers, leading on open sourcing research code, and presenting outcomes at international conferences.
- Close to completion or holds a MSc or above in a relevant technical subject.
- Possess strong publication track record in machine learning or related fields.
- Possess sufficient specialist knowledge, research skills, and interests in deep learning and large language models to work within established research programmes.
- Possess strong technical knowledge and abilities of deep learning and large language modelling frameworks, popular open source codebases, and LLM APIs.
- Possess strong motivation and interests in developing computational infrastructure to enable large scale implementations and experimentations in large language models.
- Possess strong collaboration abilities and excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings.
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