Research Fellow (Optical Microscopy / Coherence Tomography)

The Singapore Centre for Environmental Life Sciences Engineering (SCELSE) is a unique interdisciplinary Research Centre, hosted by Nanyang Technological University (NTU). SCELSE is linking new insights in microbial sciences with expertise from emerging technologies in natural sciences to understand, harness and control microbial biofilm communities.

NTU Optical Bioimaging Centre (NOBIC, nobic.sg) provides expertise in optical imaging and microscopy to researchers at Lee Kong Chian School of Medicine (LKCMedicine) and SCELSE at NTU. Our team consists of physicists, chemists and engineers who together cover a broad range of expertise relevant to optical imaging in life and biomedical sciences, including the design and development of customised imaging systems, advanced imaging experiments or image processing and analysis.

Research Fellow – Optical Coherence Tomography (OCT)

We are seeking a motivated Research Fellow to advance optical coherence tomography (including optical coherence elastrography) technology and applications. The role involves developing OCT systems (both hardware and software) and imaging methods, conducting experimental studies, analysing data, and contributing to publications and translational research in a multidisciplinary environment.

Key Responsibilities

• Develop and optimise OCT instrumentation and imaging protocols
• Implement image processing and quantitative analysis methods
• Conduct experiments, analyse data, and validate results
• Collaborate with clinicians and scientists; prepare manuscripts and presentations

Required Qualifications

• PhD (or equivalent) in Biomedical Engineering, Optical Engineering, Physics, Electrical Engineering, Medical Physics, or a related field
• Demonstrated research experience with OCT or closely related optical imaging modalities
• Strong experimental skills in optical system design, build, alignment, and characterisation
• Proficiency in programming for data acquisition and image analysis (e.g., Python, MATLAB, C/C++, LabVIEW)
• Evidence of research productivity (peer-reviewed publications or conference presentations)
• Ability to work independently and collaboratively in a multidisciplinary setting
• Excellent written and verbal communication skills

Preferred
Experience with clinical/translational studies is an advantage.

We regret to inform that only shortlisted candidates will be notified.