Similar Jobs
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
The Data Scientist role involves designing advanced image processing solutions, applying computer vision and machine learning to engineering problems, collaborating with engineers, and developing tools to improve efficiency and innovation in manufacturing.
Top Skills:
KerasMatlabOpencvPythonPyTorchRScikit ImageTensorFlow
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead engineering and maintenance of Control and SMART Facility systems, ensuring safety, reliability, and efficiency in semiconductor manufacturing. Mentor engineers, manage projects, and advance innovative solutions.
Top Skills:
HadoopPlcPythonRScadaSQLWeb Development
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Manage engineering and maintenance for mechanical facilities systems, lead expansion projects, improve system reliability, and enforce safety and maintenance standards.
Top Skills:
AribaHvacSAP
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
How You’ll Make an Impact
As a Systems Design Engineer in our qPCR/dPCR Platform R&D team, you’ll contribute to the development of advanced real-time and digital PCR systems that help scientists and clinicians uncover insights from genetic information. You will help define, design, integrate, and verify system solutions that connect hardware, software, assays, and algorithms into platforms for life science and diagnostic applications.
What You’ll Do
System Definition and Design
- Support the definition of system-level requirements and interfaces for integrated qPCR/dPCR instruments.
- Contribute to architecture discussions and trade-off analyses balancing performance, manufacturability, and cost.
- Develop and maintain system documentation, design inputs, and requirement traceability in alignment with quality and regulatory standards.
System Integration and Testing
- Conduct hands-on integration, testing, and resolving problems across hardware, software, and assay subsystems.
- Carry out experiments and verification studies to characterize system performance and identify root causes of issues.
- Apply systems engineering tools and methods (DOE, FMEA, RCA, statistical analysis) to guide design improvements.
- Support prototype build, configuration control, and test data analysis during system development cycles.
Collaboration and Communication
- Partner with multi-functional teams including Mechanical, Electrical, Software, and Assay Engineering to ensure cohesive system functionality.
- Collaborate with Manufacturing, Quality, and Service teams to support design transfer and validation activities.
- Summarize and present test results, analyses, and findings through clear technical documentation and presentations.
Continuous Improvement
- Contribute to model-based system design and simulation efforts to predict and optimize performance.
- Stay on top of emerging technologies and standard methodologies in systems engineering, instrumentation, and qPCR/dPCR technologies.
How You’ll Get Here
Education & Experience
- Bachelor’s degree in Engineering (Mechanical, Electrical, Systems, or Software) or Applied Physics with 5+ years of experience developing complex instruments; or
- Master’s/Ph.D. with 0–3 years of proven experience in life science or diagnostic product development.
Technical Expertise
- Strong, hands-on background in prototype development, integration, and testing of electro-mechanical or optical instrumentation.
- Understanding of thermal control systems, fluidics, optics, detection technologies, and signal processing relevant to qPCR/dPCR platforms.
- Familiar with systems engineering processes, from requirements gathering through verification and validation.
- Proficiency with tools such as SolidWorks, MATLAB, LabVIEW, Python, JMP, or similar modeling and analysis software.
- Experience in regulated product development environments (ISO 13485, FDA QSR, CE-IVD) preferred.
Personal Attributes
- Highly analytical, meticulous, and data-driven with strong problem-solving ability.
- Effective collaborator who builds strong relationships across fields and functions.
- Communicates clearly, both in writing and in technical discussions.
- Self-motivated and adaptable in a fast-paced, matrixed R&D environment.
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
