We learn more about the PhD internship programme hosted by Mastercard’s Dublin Tech Hub and ML-Labs from some of its key collaborators.
Like the rest of the world, Ireland is preparing for a future driven by new technologies. A critical aspect of this is finding the people with the right skills to push boundaries and give businesses a competitive edge.
Mastercard’s Dublin Tech Hub is attracting these people through its partnership with ML-Labs, which is a collaboration between University College Dublin (UCD), Dublin City University and Technological University of Dublin funded by the Science Foundation Ireland Centres for Research Training programme.
Together, the group is hosting a new PhD internship to help students from ML-Labs’ machine learning programme find their feet in industry. We spoke to Mastercard’s Dr Steve Flinter, UCD’s Dr Brian Mac Namee and PhD candidate Sagar Saxena to learn more.
The PhD internship is a unique and mutually beneficial programme for both Mastercard’s Dublin Tech Hub and ML-Labs. Flinter, who is vice-president of AI and machine learning at Mastercard Labs, explained: “This programme is going to give us access to top-grade PhD candidate students.
“Our aim for the programme is that we can support the training of those PhD students to help them get to a point where they can translate their training and their education into industry once they’ve graduated.”
Through the internship, PhD students work with one of the teams at Mastercard Labs for four months. Saxena is the first Mastercard intern on the programme. He’s interested in what Flinter described as a “very topical area”, but one that Mastercard hadn’t researched before Saxena joined the company – explainable AI for time series.
Speaking about his time on the PhD internship so far, Saxena said that the team had been supportive. He said: “All in all, working in Mastercard seems to be a game-changer and I think the experience that I’ve accrued here would help me shape my future for the better.”
For PhD candidates who want to move from academia into industry, Mac Namee explained how the internship programme can help. “It’s designed to be accessible to applicants from all kinds of different backgrounds,” he said.
“So whether you’re interested in working on new and exciting machine learning algorithms or bringing machine learning into a new area, or even looking at the societal impacts of machine learning, there’s a place for you.”