Research Associate: Web MVP for AI Property Valuations

University of Manchester; Manchester; On-site; GBP 34,000 - 48,000; Full time

Benefits offered by this job

Generous pension

Annual leave 29 days

Ride to work/EV scheme

Job summary

University of Manchester seeks a motivated Research Associate to build a client-facing MVP for the GreenAVM project. You will collaborate with the PI and Co-I to wrap the GreenAVM model into a web application and deliver a working prototype for demonstrations.

Role focuses on front-end/back-end development, cloud deployment, live data integration and SHAP-based explainability visualisations to help non-technical stakeholders understand outputs.

Qualifications

• Degree in computer science or a related discipline.
• Experience building web applications (full-stack or back-end).
• Proficiency in Python and web frameworks (Flask, Django, FastAPI or Streamlit).
• Experience deploying applications to cloud platforms (AWS, Azure, GCP).
• Experience with API integration and external data sources.

Responsibilities

• Develop a web-based application wrapping the AutoGluon valuation model for client-facing demonstrations.
• Integrate public data feeds (Land Registry, EPC Register) for live valuations.
• Implement SHAP-based explainability visualisations for interpretable outputs.
• Deploy the prototype to a cloud environment (AWS, Azure) for demonstrations.
• Document architecture, codebase, data pipelines and deployment configurations.

Skills

Web development

Python

Cloud deployment

API integration

Full-stack/Back-end

Education

Bachelor’s degree in computer science / software engineering

Master’s degree

PhD

Tools

Flask

Django

FastAPI

Streamlit

Job description

University of Manchester seeks a motivated Research Associate to build a client-facing MVP for the GreenAVM project. You will collaborate with the PI and Co-I to wrap the GreenAVM model into a web application and deliver a working prototype for demonstrations.

Role focuses on front-end/back-end development, cloud deployment, live data integration and SHAP-based explainability visualisations to help non-technical stakeholders understand outputs.