About the role
AI summarisedResearch Scientist role at ARTC focusing on predictive quality for advanced manufacturing. The position involves leading R&D of novel AI architectures fusing vision and temporal data, developing root cause analysis methods, and implementing knowledge graphs with LLMs/VLMs for automated quality sentencing.
ResearchFull-time
Key Responsibilities
- Lead the research and development of novel AI architectures that fuse vision data with temporal manufacturing process data to predict final product quality.
- Develop advanced methodologies for Root Cause Analysis (RCA), moving beyond correlation to establish causal links between process variables and inspection outcomes.
- Design and implement Knowledge Graphs and semantic reasoning layers that integrate domain expertise with LLMs/VLMs to automate 'final sentencing' and provide explainable AI (XAI) insights.
- Architect and fine-tune state-of-the-art multimodal models to enable text-promptable vision inspection and contextual decision-making.
- Pioneer the use of Temporal Transformers or Physics-Informed Neural Networks (PINNs) to analyze complex manufacturing time-series data for anomaly detection and yield prediction.
- Document research in high-impact internal reports or patent filings and stay at the forefront of AI/ML literature to maintain the institute competitive edge.
- Provide technical oversight for QC/QA governance frameworks and mentor junior engineers in data integrity and model validation.
Requirements
- Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related quantitative field is mandatory.
- Demonstrated experience in publishing or developing innovative algorithms in Computer Vision, Predictive Analytics, or Multimodal AI.
- Deep understanding of AI-based image segmentation, classification and time-series analysis and signal processing.
- Hands-on experience with Knowledge Graphs, ontologies, or graph neural networks (GNNs).
- Strong background in Root Cause Analysis (RCA) and statistical process control.
- Advanced Python programming skills.
- Ability to drive research projects from conceptualization to a deployable 'target product.'
- Exceptional ability to communicate complex scientific concepts to both technical peers and non-AI manufacturing stakeholders.