Research Fellow (Machine Learning in Chemical Engineering), ChBE 1

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The National University of Singapore invites applications for a Research Fellow to collaborate with the Principal Investigator on research projects using machine learning in chemical processes and optimization problems.

You will help develop machine learning models and control systems for both theoretical work and practical applications, contributing to high-impact publications and advancing data-driven decision making in chemical engineering.

Qualifications

• PhD in chemical engineering, control engineering, CS or systems engineering.
• Strong math, modeling, programming, and scientific writing skills.
• Experience in dynamic/data-driven modeling or TEA/LCA or control theory.

Responsibilities

• Collaborate with the Principal Investigator on ML in chemical and optimization projects.
• Develop machine learning models and control systems for theory and applications.

Skills

Math

Modeling

Programming

Scientific writing

Education

PhD in relevant area

Tools

Aspen

COMSOL

CFD

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

• The Research Fellow will work closely with the Principal Investigator on several research projects on using machine learning in chemical and optimization problems
• The Research Fellow will help to develop machine learning models and control systems for both theory and applications

Job Requirements

• 1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc.
• 2. The candidates should have strong math, modeling, programming, and scientific writing skills, and prior experience in at least one of the following areas:
  • a. Chemical process modeling for electrochemical surface engineering processes and/or pharmaceutical crystallization, with expertise in dynamic/data-driven modeling, optimization, Aspen, COMSOL, or CFD
  • b. Techno-economic analysis (TEA) & life-cycle assessment (LCA) for chemical, energy, or biomanufacturing processes, based on simulation models in Aspen, COMSOL, etc.
  • c. Control theory & applications — including nonlinear systems, MPC, reinforcement learning, stability analysis, etc.