Summary of Post The Cardiovascular Research Institute (CVRI) Dublin is seeking an ambitious AI Software Engineer / Postdoctoral Researcher to spearhead the translation of research-grade AI models into a production-ready Clinical Decision Support System (CDSS) .
In this role, you will be responsible for the "last mile" of innovation.
You will take high-performance deep learning models for tricuspid valve assessment and Right Ventricular (RV) function and architect the software environment required to deploy them within a clinical workflow.
This involves building the infrastructure for real-time inference, managing the software development lifecycle (SDLC), and ensuring the final tool meets the rigorous technical standards required for clinical testing and validation.
Based at RCSI/CVRI, you will work at the intersection of software engineering and clinical AI to deliver a tool that standardizes precision patient selection.
Specifically, the duties of the post are: The applicant will work in Prof. Soliman's lab at both RCSI and Mater Private Hospital.
Key Responsibilities The AI Software Engineer/Postdoc is responsible for translating research outcomes into clinical tools.
Specifically, the duties of the post are: CDSS Architecture: Design and build a modular, scalable software architecture for the Clinical Decision Support System that integrates multi-modal AI outputs (Imaging and NLP).
1. Model Deployment: Translate research-grade Python scripts/notebooks into optimized, production-ready code; implement containerization (e.g., Docker) and API structures for clinical tool integration.
2. Interface Development: Collaborate with clinical users to design and implement user-friendly interfaces (UIs) that visualize complex AI metrics (like TR severity and RV-PA coupling) intuitively.
3. System Integration: Manage the pipeline for DICOM data ingestion and ensure the software can interface effectively with hospital imaging databases (PACS/VNA) for research validation.
4. Technical Documentation: Maintain rigorous documentation of the software codebase, version control, and system requirements to support future regulatory (CE/FDA) submissions.
5. Validation Support: Lead the technical deployment of the tool for Task 8.5, ensuring system stability during blinded comparisons by expert cardiologists.
Requirements Essential: Qualification: PhD in Computer Science, Software Engineering, or a related field with a focus on Machine Learning deployment.
Research or industrial experience in software engineering and AI implementation.
Software Mastery: Expert proficiency in Python and standard AI frameworks ( PyTorch/TensorFlow ), alongside experience in full-stack or backend development.
Engineering Best Practices: Proven experience with version control (Git), CI/CD pipelines, and software testing methodologies.
Problem Solving: A track record of taking complex algorithms and optimizing them for performance and reliability in real-world environments.
Desirable: • Experience with EHR/clinical data and imaging integration for software tools.
• Knowledge of multi-objective optimization and time-series analysis.
• Publications in high-impact journals related to AI deployment or software engineering.
• Experience with medical imaging libraries (MONAI, SimpleITK) or web-based medical viewers (OHIF/Cornerstone).
• Familiarity with medical data standards such as DICOM and HL7/FHIR .
• Previous experience developing software under Quality Management Systems (e.g., ISO *****).
We are all too aware that imposter syndrome and the confidence gap can sometimes stop fantastic candidates putting themselves forward, so please do submit an application — we'd love to hear from you.