Designing a Talent-Matching Ecosystem for a Large University

The platform makes institutional talent discoverable: structured professional profiles on one side, project and organisational needs on the other, and a matching layer between them.

Expertise inside a large institution is real but invisible. Teams recruit through personal networks because there is no shared, structured representation of skills and availability.

The design challenge was to make profile creation worth the effort while keeping matching legible to both sides.

• Professionals and students building profiles
• Project teams and units describing needs
• Institutional administrators managing the ecosystem

Profiles were designed as structured data rather than free text, so matching could be explainable and search could stay precise across a very heterogeneous population.

A shared skills and domains vocabulary connects profiles, opportunities and search, allowing several distinct journeys to operate on the same underlying model.

Onboarding is progressive: a usable profile first, depth later. Opportunity creation mirrors the same vocabulary so both sides describe work in comparable terms.

• Progressive onboarding with visible profile completeness
• Structured taxonomy instead of free-form skill entry
• Matches presented with the reasons behind them
• Role-specific navigation over one generic dashboard

Matching is presented as a ranked, explainable recommendation that people can refine — not an automatic assignment.

A component system covering profiles, forms, taxonomies, search and listing patterns supports the platform's institutional scale and multiple roles.

Long structured forms were designed with clear labels, grouped fieldsets, keyboard-friendly controls and accessible error handling.

In multi-sided institutional products, a shared vocabulary is the real product. Interface quality depends on how well both sides describe the same thing.