Research Assistant

The University of Stirling Management School seeks to appoint a Research Assistant to support the development of an AI-enabled Cultural Brand Diagnostic Application as part of an ESRC Impact Acceleration Account (IAA)-funded research commercialisation project.

The project aims to develop an early-stage Minimum Viable Product (MVP) that enables marketing practitioners to evaluate and optimise the cultural fit of brand communications across international market contexts.

The system will allow users to:

1. Upload selected marketing assets (e.g. campaign visuals, copy, video content)
2. Configure analytical parameters via a simplified dashboard (e.g. target segment, geographic context, analytic lenses)
3. Execute an AI-supported cultural brand fit analysis
4. Receive a structured diagnostic output including

In addition to supporting cultural fit assessment, the system will incorporate configurable analytic lenses designed to surface potential autonomy-sensitive risks associated with campaign deployment (e.g. preference instability, symbolic over-assertion, or narrative misalignment within local contexts). These features are intended to support reflectively mediated optimisation decisions prior to campaign deployment.

The developed system will not constitute a full commercial MVP but must enable end-to-end execution of a complete cultural diagnostic chain within a defined range of analytic configurations.

The Research Assistant will contribute to the design and implementation of a modular diagnostic engine that enables marketing practitioners to configure, execute, and interpret AI-assisted cultural brand fit analyses within a structured decision-support environment.

This will involve:

• developing prompt-driven analytic workflows for cultural inference across marketing assets
• connecting user-selected analytic configurations to model inference pathways
• implementing a functional MVP interface through which users can upload assets, configure analyses, execute diagnostics, and receive structured outputs

In doing so, the successful candidate will contribute to the development of optimisation environments that measurably influence campaign configuration decisions in autonomy-relevant directions prior to deployment.

The Research Assistant will:

• Develop prompt-driven analytic workflows using GPT-class APIs
• Assist in structuring analytic configuration pathways within the diagnostic engine
• Contribute to the development of a functional MVP interface enabling asset upload, analytic configuration, and diagnostic execution
• Connect user-selected analytic lenses (e.g. cultural resonance, norm conflict detection, symbolic intensity) to inference pathways within the application
• Support the integration of asset input, analytic configuration, and diagnostic output pipelines
• Contribute to the development of structured output displays and recommendation pathways
• Assist in implementing logging functionality to capture user configuration and override behaviour within the application environment
• Collaborate with project partners on MVP development and testing processes
• Assist with documentation of analytic logic for research and commercialisation purposes