[Internship] 3 computer vision projects: heart rate from video, makeup colour analysis, shelf product monitoring
Merit First. Top engineers get in for free, and those who transfer from abroad will receive a travel and accommodation grant.
Learn by doing. Minimal teaching. Desks and environment are organised to support small project teams, agile co-development, interactions with mentor.
Real world projects, no simulations. Our partners sponsor top engineers to solve real challenges. This may convert into the best job you ever had.
The School of AI programme (free for participants, sponsored) at Pi School in Rome, Italy is running its 5th session from October 28th to December 21st 2019.
Attendance is free of charge for participants, who get expenses (flight, accommodation) refunds up to 2000 EUR.
We are looking for fellows with a strong vision background to work on three challenging computer vision projects which have been submitted by our sponsors: - heart rate and oxygenation rate detection on baby monitor video stream - make-up colour recommender: machine vision for beauty - detecting removed drink in a camera-equipped, self-service vending machine
If you or people you know would like to work on these topics with state of the art methods and world class coaching and mentoring, please apply on our web page (google: "pi campus school of ai").
The programme is fully funded by industry sponsors, which allows us to make it free for fellows. We take on challenging business problems, and turn them into machine learning problems. Applicants go through a recruitment-like selection procedure, and the strongest ones are invited to attend Pi School in Rome for 8 weeks in Q4 2019. For each project, we find mentors: eg Google Brain researchers, startup CTOs, ML professors at university... In each session, we have 20 to 30 participants on site, which form a beautiful, strongly international community of AI enthusiasts.
Projects are hands-on, real industry challenges, running in a very short timespan, so they're sometimes really tough: that's why our on-site coaches are here to help with AI project strategy (and we think we're quite good at this), as well as any tech or modelling issue.
Our projects tend to be more fun (and more "condensed") than the typical internship, because we prepare them for you beforehand: as much as possible, we try to have everything ready (data, metrics, understanding of business context) for when you arrive, so that we can focus on statistical model building during the session. (Then of course, real industry problems aren't always smooth sailing :-)...)
We call them "externships" because they're not carried out with the company whose problem you're working on, but within a space dedicated to AI projects instead !