Postdoctoral Associate (Machine Learning): The Singapore-MIT Alliance for Research & Technology (SMART) is seeking highly motivated and talented individuals for the position of Postdoctoral Associate in Resource-Efficient Machine Learning. This role focuses on advancing state-of-the-art methodologies aimed at improving computational efficiency in large-scale AI systems.
Postdoctoral Associate (Resource-Efficient Machine Learning)
Designation
Postdoctoral Associate (Resource-Efficient Machine Learning)
Job Details
| Category | Details |
|---|---|
| Research Area | Resource-Efficient Machine Learning, Foundation Models, AI Optimization |
| Location | SMART Centre, Singapore |
| Eligibility/Qualification | – Doctoral degree in Computer Science, Machine Learning, Statistics, Mathematics, or related discipline. – Experience with large-scale deep learning models and modern ML frameworks (e.g., PyTorch, JAX). – Proven track record in high-quality research contributions. – Proficiency in high-performance computing and modern ML pipelines. |
Job Description
- Develop resource-efficient machine learning methods to enhance the computational efficiency of large-scale AI systems, including foundation models.
- Design and implement next-generation algorithms and architectures to address existing resource constraints.
- Prototype and evaluate complex machine learning systems, assessing performance and scalability of novel ideas.
- Collaborate with research staff and students to publish findings in top-tier conferences and journals.
- Provide mentorship to PhD students and research engineers, fostering a collaborative research environment.
How to Apply
Interested applicants should send their full CV/resume, cover letter, and a list of three references (including names and contact information) to the SMART Hiring Committee. Please complete the SMART Job Application Form and upload it with your application.
Last Date to Apply
Applications will be accepted until [Specific Date Needed]. Only shortlisted candidates will be notified.
