Lead Research Engineer (FAB)

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A leading research organization in Singapore is seeking an Etch Process Engineer to support research and development in optimizing plasma and wet etch processes. This role demands hands-on experience and proficiency in data analytics to enhance process performance. Candidates should hold a relevant degree and possess knowledge of machine learning applications. The successful applicant will work collaboratively in a challenging semiconductor environment, leveraging AI/ML for process improvement.

Qualifications

• Hands-on experience with plasma etch or wet etch processes in semiconductor environments.
• Knowledge of SPC, DOE, and structured problem-solving methodologies.
• Experience working in cleanrooms with a strong understanding of semiconductor process flow.

Responsibilities

• Develop and optimize plasma etch and wet etch processes for R&D.
• Analyze etch performance using statistical analysis and automated dashboards.
• Troubleshoot plasma etch equipment issues and collaborate with engineers.

Skills

Plasma etch process optimization

Data analytics using Python

Machine learning applications

Statistical process control (SPC)

Education

Bachelor's or Master's degree in Materials Science, Chemical Engineering, Electrical Engineering, Mechanical Engineering, Physics, or related fields

Tools

Python

MATLAB

JMP

Job description

Etch Process Engineer – R&D

The Etch Process Engineer supports research and development by designing, developing, and optimizing plasma etch and wet etch processes for advanced materials, device integration, and next‑generation packaging technologies. The role involves hands‑on process development, thin‑film characterization, and data‑driven decision-making, leveraging AI/ML for faster optimization, predictive analysis, and improved process robustness.

Key Responsibilities

Process Optimization

• Develop, qualify, and optimize plasma etch (dry etch) and wet etch processes for R&D, prototyping, and early‑stage technology enablement.
• Characterize etch profiles, selectivity, uniformity, CD control, and surface quality using industry‑standard metrology tools.
• Design and execute DOE experiments to identify key process parameters, reduce variability, and improve process stability.
• Apply AI/ML techniques (e.g., predictive modeling, pattern recognition, clustering) to accelerate process tuning and optimize etch performance.

Data Analytics & Process Control

• Monitor, analyze, and control etch performance using SPC, statistical analysis, and automated data analytics dashboards.
• Use machine learning or algorithmic tools to detect process drifts, predict equipment instability, and improve fault detection.
• Develop scripts or workflows to automate data extraction, analysis, and visualization for engineering insights.

Equipment & Operations Support

• Troubleshoot plasma etch and wet etch equipment issues, collaborating closely with equipment engineers and tool vendors.
• Support installation, calibration, chamber matching, and maintenance of etch systems (e.g., RIE, ICP, DRIE, isotropic/anisotropic wet etch tools).
• Drive continuous improvement to enhance tool uptime, wafer uniformity, and process repeatability.

Materials & Integration

• Evaluate material interactions, etch chemistries, mask selectivity, and post‑etch surface conditions for integration with downstream processes.
• Conduct root‑cause analysis on defects related to etch residue, profile distortion, microloading, and plasma damage.
• Work closely with integration, metrology, and reliability teams on material stack development and new device structures.

Documentation & Reporting

• Maintain detailed documentation including process recipes, SOPs, experiment records, yield and defect analysis, and improvement reports.
• Present technical results, data insights, and recommendations to R&D teams and management.

Job Requirements

• Bachelor's or Master's degree in Materials Science, Chemical Engineering, Electrical Engineering, Mechanical Engineering, Physics, or related fields.
• Hands‑on experience with plasma etch (e.g., RIE, ICP, DRIE) or wet etch processes in semiconductor or advanced packaging environments.
• Proficiency in data analytics using Python, MATLAB, JMP, or similar statistical tools.
• Familiarity with AI/ML applications in process engineering (predictive models, cluster analysis, anomaly detection).
• Knowledge of SPC, DOE, and structured problem‑solving methodologies (8D, FMEA, root‑cause analysis).
• Experience working in cleanrooms, with strong understanding of semiconductor process flow and equipment safety.
• Strong analytical mindset, excellent problem‑solving skills, and ability to manage complex datasets.