University of Melbourne

Using machine learning to connect researchers to new funding streams

We researched, designed and developed an aggregation tool to connect academics with relevant grant opportunities to support their research.

A man sitting at a table doing a card sort. Cards cover the table, and each card has a product feature or detail, such as notifications, funding amount and pre-filled forms. He is looking at the cards and choosing which ones are most valuable to him.
Outcomes

  • A digital product that matches researchers to relevant grants with algorithms and machine learning

  • Prioritised feature backlog and recommended delivery roadmap for future development

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Avoiding missed opportunities

Researchers across Australia are often applying for the same narrow range of research grants each year. This results in those grants becoming more competitive and harder to win – and a lot of researchers’ effort being wasted in the process.

The University of Melbourne wanted to develop a tool to support researchers when they’re looking for funding to support their research – and connect them to a much wider range of grant opportunities.

Paper Giant was brought in as a design and development partner to understand what the researchers would need from the tool and assist with development of the product.

Screenshot of a grant opportunities dashboard, showing three of eight new opportunities. Each opportunity includes the organisation name, funding amount and closing date. There are buttons that allow the user to accept or reject each opportunity.
Screen 1/4 of clickable prototype. This screen shows how users can discover new funding opportunities. Each opportunity has the organisation name, closing date and funding amount. Users can accept or reject each opportunity.
Screen 2/4 of clickable prototype. This screen allows the user to accept or reject an opportunity.
Screen 3/4 of clickable prototype. This screen shows how users can personalise the opportunities they receive by adding keywords to their profile. This example shows keywords such as art conservation, heritage and government.
Screen 4/4 of clickable prototype. This screen shows the notifications settings. Users can select how often they want to be notified about new opportunities. Options include weekly, monthly and never.

Clickable prototype of opportunities tool.

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Simultaneous research and development

Our approach was to develop the tool and conduct our research simultaneously. This meant we could quickly utilise a mix of clickable and live prototypes to test new aspects of the user experience with participants.

This enabled us to understand the user journey end to end, identify the most valuable opportunities to pursue and iteratively build upon what we were learning during interviews. The result is a user experience and visual brand that effectively meets the needs of researchers.

A map of three core user journeys. The map outlines each point that a user will interact with the tool.

User journeys created during the project

MVP Delivery

We mapped out clear user journeys and integrated complicated grant data from multiple sources with algorithmic learning to enable the tool to continually refine the grant opportunities sent to researchers.

Our deep understanding of API integration and backend systems enabled us to quickly conceptualise, build and test front-end templates and incorporate them into a pilot running with several faculties across the university.

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