Research Fellow (Machine Learning and AI for Science)

National University of Singapore; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

An established industry player is seeking post-doctoral research fellows to join their innovative team at the Institute for Functional Intelligent Materials. This role focuses on pioneering research in machine learning and its applications in materials and quantum sciences. Candidates will collaborate with leading experts, engaging in data-driven multiscale modeling and developing new architectures for dynamic systems. The position offers a unique opportunity to contribute to groundbreaking research that pushes the boundaries of science and technology. If you are passionate about machine learning and eager to make a significant impact, this is the perfect opportunity for you.

Qualifications

• PhD in Applied Mathematics, Computer Science, Physics or related fields required.
• Strong publication record in top machine learning conferences and journals.

Responsibilities

• Conduct cutting-edge research in machine learning theory and algorithms.
• Collaborate with Principal Investigators on various scientific applications.

Skills

Machine Learning

Deep Learning

Python

Dynamical Systems

Computational Physics

Education

PhD in Applied Mathematics

PhD in Computer Science

PhD in Physics

Tools

Jax

PyTorch

Job description

Company description:

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job description:

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The Institute for Functional Intelligent Materials (I-FIM) is looking for post-doctoral research fellows to work on topics in machine learning and its scientific applications. The successful candidate will work with Principal Investigators in I-FIM on these topics. The main responsibilities of the position include conducting cutting-edge research in machine learning theory and algorithm research, with applications to materials and quantum sciences. Topics include (but are not limited to) the following:

• Data-driven multiscale modelling
• Approximation and optimisation theory of new architectures with applications in dynamics
• Learning and controlling deterministic and stochastic dynamics

Job Requirements

Qualifications / Discipline:

• PhD in (Applied) Mathematics, Computer Science, Physics or related fields

Skills

• Strong knowledge in machine learning and deep learning
• Familiarity with basic theory of dynamical systems, ODEs, PDEs, and stochastic processes
• Knowledge in computational physics, chemistry are desirable
• Ability to code in Python with at least one of the popular deep learning frameworks, e.g. Jax, PyTorch

Experience

• Academic research with strong publication record. The candidate should have published in top machine learning conferences and journals, such as ICML, ICLR, NeurIPS, JMLR, and/or top journals in mathematics and applied sciences

More Information

Location: Kent Ridge Campus
Organization: Institute for Functional Intelligent Materials
Department : Research Groups
Job requisition ID : 28602