Data, AI & Algorithm Internship - Philips Avent Experience Innovation

Job Description:

Job Title
Data, AI & Algorithm Internship - Philips Avent Experience Innovation

Job Description

Start Date: As of September 2026
Duration: at least / 6 months
Type: Internship (non- thesis)
Weekly Presence: 40h (minimum 32h)
Location: Eindhoven area or Shenzhen, with guidance from the Eindhoven team
Mentor: Gabriele Papini

Internship Title
586189 Data, AI & Algorithm Internship - Philips Avent Experience Innovation

Your role:
At Philips Avent, we design meaningful innovations that support parents and babies in everyday moments of care. Within our Experience Innovation team, we explore the next generation of smart baby care products, including connected propositions such as our Smart Parenting portfolio and SenseIQ-based features.
We are looking for a talented student who can help turn large real-world datasets into meaningful product functions. This is not only about analysing data or building models in isolation. It is about understanding what parents need, what signals are available, what is "good enough" in a real product context, and how data, AI and algorithms can create reliable reassurance.
You will work under the guidance of our Data, AI & Algorithm Lead, Gabriele Papini, and collaborate with engineers, designers, researchers and proposition leads across Eindhoven, Amsterdam and Shenzhen.
In this role, you will:
* Explore SenseIQ and connected product data to identify patterns, opportunities and potential reassurance features.
* Translate consumer needs into measurable signals, data requirements, algorithm logic and performance metrics.
* Build and iterate on data analysis pipelines and algorithm prototypes, mainly in Python.
* Help define what "good" looks like for a product function, including reliability, false alarms, edge cases and user relevance.
* Support validation of early algorithm concepts under real-world variability, such as motion, noise, lighting or inconsistent user behaviour.
* Communicate insights clearly through structured analyses, visualizations and decision-ready recommendations.
* Contribute to faster experimentation by using automation, AI tooling and efficient data workflows.
You're the right fit if
* You are studying Data Science, AI, Computer Science, Applied Physics, Electrical Engineering, Biomedical Engineering, Robotics, Mechatronics or a related technical discipline.
* You are strong in Python and comfortable with data analysis, statistics and rapid prototyping.
* You enjoy translating messy real-world data into clear insights, hypotheses and functional concepts.
* You are interested in the full chain from sensor, camera or product data to algorithm to consumer-facing product function.
* Experience or curiosity in computer vision, video processing, image processing or signal extraction from visual data is a strong plus.
* You can think pragmatically about trade-offs: accuracy, reliability, false alarms, explainability and user trust.
* You have curiosity for AI tooling, automation and faster ways of working.
* You communicate clearly and can explain technical insights to non-technical stakeholders.
* You are proactive, hands-on and eager to learn in a multidisciplinary innovation team.
This role is less suited to students who only want to train models on prepared datasets, focus purely on dashboards or data reporting, or stay in abstract research without translating insights into product functions. We are specifically looking for someone who wants to work end-to-end: from data understanding to algorithm logic to meaningful user value.
Does this sound like you?
Apply now and share your resume together with relevant projects, code examples, notebooks, GitHub links or other self-made work that shows your technical curiosity, data skills and ability to translate data into meaningful product functions.
Graduation: We prefer this to be a regular 6-month internship. A graduation assignment is possible, but only if it can be clearly connected to our innovation projects and leaves enough time to contribute broadly to other team activities.

How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company's facilities. Field roles are most effectively done outside of the company's main facilities, generally at the customers' or suppliers' locations.

We offer you:
A non-stop growth opportunity within a global multinational company. In addition, we also want to renumerate you well for the opportunity. This includes:
* Monthly full-time allowance between EUR500 - EUR700 gross, depending on your education level and if you need to relocate to The Netherlands. Part-time internships receive the allowance pro-rata.
* Housing compensation. Should you need to relocate to near our office, we'll offer you a monthly allowance of EUR300,- net if location is in the vicinity of Amsterdam, EUR255,- net for all other Philips locations. To be eligible, we'll just ask for the rental contract from your landlord, and your usual home-work travel distance needs to be more than 50 km or 1.5 hours of travel time (for a one way trip).
* Travel compensation, if you are not eligible for a free public transport card; you will receive max. EUR192,- net as a monthly allowance.
* Paid holidays per internship term.
* The opportunity to buy Philips products at our Philips shop.

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
* Learn more about our business.
* Discover our rich and exciting history.
* Learn more about our purpose.

If you're interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.

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