Postdoctoral Research Fellow – AI Self-Driven Laboratory for Biology
Research Fellow I
Job Req ID: 2335
Employee Category: Research
Department: EPD Pillar
Postdoctoral Research Fellow – AI Self-Driven Laboratory for Biology
The Singapore University of Technology and Design (SUTD) invites applications for a Postdoctoral Research Fellow position in the area of AI-driven experimental systems for biology. This position is hosted within the Engineering Product Development (EPD) pillar and is part of a strategic research effort to develop next-generation AI self-driven laboratories for biological discovery.
EPD is a multidisciplinary pillar at SUTD that addresses complex technological challenges through a design-centric and systems-oriented approach. The successful candidate will contribute to an interdisciplinary research programme at the intersection of optics, electrical engineering, artificial intelligence, and experimental biology, with the aim of building closed-loop, autonomous experimental platforms that accelerate scientific discovery.
The successful candidate is expected to:
- Design and develop optical sensing and imaging systems for biological experiments (e.g. microscopy, spectroscopy, fluorescence-based readouts).
- Develop electronic and hardware control systems for laboratory instrumentation, including sensors, actuators, microfluidic devices, and automation components.
- Integrate experimental hardware with software and data pipelines to enable real-time data acquisition and closed-loop control.
- Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous decision-making.
- Build robust, scalable experimental platforms capable of long-duration and autonomous operation.
- Contribute to high-impact journal and conference publications
- Mentor graduate students and contribute to a collaborative, interdisciplinary research culture.
The candidate must have:
- A PhD in Electrical Engineering, Applied Physics, Robotics, or a closely related discipline.
- Strong background in optical systems and experimental instrumentation.
- Demonstrated experience with electronics, sensors, and data acquisition systems.
- Proficiency in programming
- Proven ability to design, build, and debug real-world experimental systems.
Candidates meeting the following criteria will be favorably evaluated:
- Prior exposure to biological, chemical, or microfluidic experimental platforms.
- Experience integrating machine learning or data-driven models with physical systems.
- Experience with laboratory automation, robotics, or autonomous experimentation.
- Ability to work effectively across disciplinary boundaries and communicate with domain scientists.
Interested candidates should submit the following documents:
- Cover letter
- Curriculum Vitae
- Brief statement (1–2 pages) describing relevant technical experience and systems built
- Names and contact details of two referees
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