Support and enhance training content such as workbooks, job aids, posters, campaign materials, and presentation decks aligned with HTQA standards and brand guidelines.
Fusion diagnostics and data analysis: Analyse and interpret experimental diagnostic data, including signal processing, data curation, diagnostic reconstruction, validation, and the development of robust analysis workflows.
11 days
ScientistA*STAR - Agency For Science, Technology And ResearchFull TimeSingapore
Area A — Scientific ML & PINNs Methodology Origination: Originate and advance PINNs methodology — design physics-constrained loss function architectures, validate digital twin ML components against domain physics (with storage domain expert), and deliver validated prototypes with complete technical documentation to implement. As the sole PINNs methodology originator on the team — this capability cannot be delegated or substituted.
As an AI Engineer, you will work with our tech team to improve our 2D/3D vision models and bring small language model (SLM) and retrieval-augmented generation (RAG) capabilities to edge devices. You will also help build the testing, validation, and documentation that meet the standards of regulators such as the HSA and FDA.
Map the current lot disposition flow with quality, product and process engineers (hold triggers, evidence gathered, decision rules, MRB, approval levels) and design the target AI-assisted flow: what is automated, what is assisted, and what stays manual.
Deliver RGSynapse, RGS’s Year 1 to Year 3 computational literacy and innovation programme, integrating computational thinking, coding, responsible AI-assisted development, digital prototyping, physical making and design thinking.
MLOps/AIOps Platform Engineering: Design and implement reusable platform components and golden paths for experiment tracking, model registry, pipeline orchestration, deployment, monitoring, feedback and retraining using Databricks, MLflow and approved AWS services.
Agentic AI Architecture: Design the end-to-end architecture for FAM agentic AI solutions, including agent orchestration, workflow design, state management, tool integration, human approval points and system interactions, using suitable frameworks such as LangGraph or CrewAI. Architecture decisions are subject to consultation with DSAD’s Platform Team.
The supervision of students from arrival to departure and in different contexts, such as recess, lunch time, school outings, ensuring their safety and well-being,