Computational implementation of intelligent schema for an assurance case model - ON-1072

Project type: Research
Desired discipline(s): Engineering - biomedical, Engineering, Engineering - computer / electrical, Computer science, Mathematical Sciences
Company: Springborne Canada, Inc
Project Length: 6 months to 1 year
Preferred start date: 06/02/2025
Language requirement: English
Location(s): GTA/Ontario, ON, Canada
No. of positions: 1
Desired education level: Master'sPhD
Open to applicants registered at an institution outside of Canada: Yes

About the company: 

Springborne is a compliance service provider dedicated to helping startups and mid-sized companies navigate complex regulatory requirements. Our mission is to accelerate the market entry of innovative healthcare products by reducing the time and cost of compliance. We specialize in agile Quality Management System (QMS) implementation and regulatory submissions, providing tailored support to streamline processes and ensure a smooth path to commercialization.

Describe the project.: 

The goal of this research project is develop a prototype software implementation of an intelligent data schema for representation of lifecycle information for complex products.

One challenge with complex products especially those built on platform technologies is maintaining traceability to requirements and assuring adequate balance of safety and effectiveness. Decisions made an earlier stage in the lifecycle are typically revisted throughout the product lifecycle. This results in a constant evolution of the platform and product, making it very challenging to maintain traceability.

Springborne has developed an innovative information schema for modeling multidimensional systems. The goal of this schema is to enable lifecycle tracking of complex products through product evolution, planned released versions, testing and risk management. Additional product atributes that are modeled include, usability, cybersecurity, and interoperability of the technology platform and product variants built on the platform.
This research project aims to implement this information schema in a graph database.

Key Tasks
• Implement schema to systematically maintain and index information
• Implement an automated information tracking system to track version history and points of use
• Integrate AI-Driven Insights to enhance rapid model population, searchability, indexing, and change control
• Ensure scalability through iterative testing and process optimization to enhance efficiency and adaptability
• Implement workflow automation rules - criteria for automated approvals, version updates, and compliance checkpoints

Required expertise/skills: 

Specific Software & Tools:
• Graph Database Applications Neo4J, AuraDB
• GraphQL e.g., Cypher
• SQL
• Gen AI for graphs e.g., GraphRAG
• Google Cloud Platform

Specific Skills:
• Familiarity with Knowledge Graphs & Ontologies
• Expertise with data Modeling & Schema Design
• Familiarity with Cloud Platforms & Integration
• Strong understanding of data Architecture & Indexing for complex multidimensional data models

Optional Assets:
• AI & Automation: Knowledge of NLP, AI-driven document processing, and workflow automation
• Familiarity with security & Compliance architecture, Understanding of role-based access control (RBAC), encryption, and data integrity measures
• API Development & Integration: Building RESTful APIs for interoperability with enterprise systems