Research Fellow, Bioelectronics & ML Materials

National University of Singapore; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

The National University of Singapore invites applications for a Research Fellow in Bioelectronics & Machine Learning within the Electrical and Computer Engineering and Materials Science and Engineering departments.

The successful candidate will conduct independent and collaborative research on advanced materials, sensors, and data-driven analysis, publish papers, and contribute to grant deliverables while working in a dynamic, multidisciplinary team.

Qualifications

• PhD in a relevant field (Chemistry, Materials Science, Chemical Engineering, Physics)
• Strong experimental research skills with publications
• Experience in advanced materials synthesis, characterisation, and device fabrication
• Familiarity with computational modelling or data-driven analysis preferred
• Ability to work independently and in multidisciplinary teams
• Open to fixed term contract

Responsibilities

• Conduct independent and collaborative research in advanced materials and sensing technologies.
• Design, synthesise, fabricate, and characterise functional materials and devices.
• Perform experimental studies and computational modelling to understand material properties and device performance.
• Analyse data using appropriate statistical and machine learning tools where applicable.
• Publish journal papers and meet grant deliverables.
• Perform routine laboratory duties.
• Assist with other tasks and responsibilities as assigned by their immediate supervisor.

Skills

Experimental research

Publication track record

Materials synthesis

Device fabrication

Computational modelling

Data-driven analysis

Independent work

Collaborative work

Education

PhD in Chemistry, Materials Science, Chemical Engineering, Physics, or a related discipline

Tools

Computational modelling tools

Statistical data analysis

Job description

The National University of Singapore invites applications for a Research Fellow in Bioelectronics & Machine Learning within the Electrical and Computer Engineering and Materials Science and Engineering departments.

The successful candidate will conduct independent and collaborative research on advanced materials, sensors, and data-driven analysis, publish papers, and contribute to grant deliverables while working in a dynamic, multidisciplinary team.