A
Agency for Science, Technology and Research (A*STAR)via Indeed
Research Engineer/ Senior Research Engineer (FAB Data & Automation), (NSTIC), IME
SGPosted 4mo ago
ResearchSeniorFull-time#python#pytorch#tensorflow#computer-vision#reinforcement-learning#aws#gcp#azure#spark
Not sure if you're a good fit?
Upload your resume and TixelJobs AI will compare it against Research Engineer/ Senior Research Engineer (FAB Data & Automation), (NSTIC), IME at Agency for Science, Technology and Research (A*STAR). Get a match score, missing keywords, and improvement tips before you apply.
Free preview · Your resume stays private
About the Role
Key Responsibilities
Design, develop, and implement scalable data pipelines to ingest, clean, and structure high-volume, high-velocity data from fab tools (e.g., sensors, MES, EDA, APC systems).
Apply advanced analytics, machine learning, and AI techniques (e.g., computer vision, time-series forecasting, anomaly detection, reinforcement learning) to improve manufacturing outcomes.
Build predictive and prescriptive models for applications such as:
Yield prediction and root cause analysis
Equipment health monitoring and predictive maintenance
Real-time process control and fault detection
Defect classification and pattern recognition
Collaborate with cross-functional teams to translate business problems into analytical frameworks and measurable KPIs.
Deploy and monitor ML models in production environments, ensuring reliability, scalability, and compliance with fab data governance standards.
Stay current with emerging AI/ML technologies and assess their applicability to semiconductor manufacturing challenges.
Document methodologies, share insights through dashboards/reports, and support continuous improvement initiatives.
Required Qualifications
Minimal Bachelor in Data Science, Computer Science, Electrical Engineering, Industrial Engineering, Applied Mathematics, or a related field preferred.
2+ years of experience applying data analytics and/or machine learning in semiconductor manufacturing or fab automation.
Knowledge of semiconductor processes (e.g., lithography, etch, deposition) or equipment data standards (SECS/GEM, GEM300)
Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL.
Experience working with time-series data, sensor data, or structured/unstructured manufacturing data.
Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (e.g., Spark, Kafka).
Understanding of statistical methods, experimental design, and model validation techniques.
Excellent problem-solving, communication, and teamwork skills.
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.
Type of Employment : Full-Time
Minimum Experience : 2 Years
Work Location : Science Park
Design, develop, and implement scalable data pipelines to ingest, clean, and structure high-volume, high-velocity data from fab tools (e.g., sensors, MES, EDA, APC systems).
Apply advanced analytics, machine learning, and AI techniques (e.g., computer vision, time-series forecasting, anomaly detection, reinforcement learning) to improve manufacturing outcomes.
Build predictive and prescriptive models for applications such as:
Yield prediction and root cause analysis
Equipment health monitoring and predictive maintenance
Real-time process control and fault detection
Defect classification and pattern recognition
Collaborate with cross-functional teams to translate business problems into analytical frameworks and measurable KPIs.
Deploy and monitor ML models in production environments, ensuring reliability, scalability, and compliance with fab data governance standards.
Stay current with emerging AI/ML technologies and assess their applicability to semiconductor manufacturing challenges.
Document methodologies, share insights through dashboards/reports, and support continuous improvement initiatives.
Required Qualifications
Minimal Bachelor in Data Science, Computer Science, Electrical Engineering, Industrial Engineering, Applied Mathematics, or a related field preferred.
2+ years of experience applying data analytics and/or machine learning in semiconductor manufacturing or fab automation.
Knowledge of semiconductor processes (e.g., lithography, etch, deposition) or equipment data standards (SECS/GEM, GEM300)
Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL.
Experience working with time-series data, sensor data, or structured/unstructured manufacturing data.
Familiarity with cloud platforms (AWS, Azure, or GCP) and big data tools (e.g., Spark, Kafka).
Understanding of statistical methods, experimental design, and model validation techniques.
Excellent problem-solving, communication, and teamwork skills.
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.
Type of Employment : Full-Time
Minimum Experience : 2 Years
Work Location : Science Park
Ready to apply?
This job is active. Apply now to get in early.