
Internship | Teaching a Drone Where to Look for Better 3D Reconstructions
Make your mark on our time. Become an intern at TNO!
About this position
At TNO, the Netherlands Organisation for Applied Scientific Research, researchers work on turning cutting-edge science into technology that matters in the real world — from healthcare and energy to defense and mobility. Within TNO's work on autonomous systems, one recurring challenge is teaching machines to see, understand, and act in complex, unpredictable environments — the same kind of everyday messiness that makes tasks trivial for humans but remarkably hard for robots. This internship sits within that effort, focusing on drones that can autonomously make a good 3D reconstruction.
You will study a drone that plans its own flight path for 3D scanning, deciding in real time where to fly next based on what it has already captured, rather than following a fixed grid or orbit and hoping the result reconstructs well. Using fast, lightweight 3D foundation models (like VGGT or MapAnything) that estimate rough scene geometry from the live camera feed, the drone builds a running sense of which parts of the scene are well covered and which still need better angles, distances, or overlap — without ever needing to build the slow, high-quality 3D Gaussian Splat reconstruction mid-flight. On top of this general coverage strategy, the drone can also be told, in plain language, about specific objects of interest ("the red fire hydrant"), which it locates using open-vocabulary detection models and then prioritizes for extra close-up passes until it has captured enough varied viewpoints to reconstruct that object well. The result is an adaptive, semantically aware flight planner that actively chases reconstruction quality rather than just flying a predetermined path, with the thesis delivering both a working planning pipeline (in simulation and/or on a real drone) and an empirical study of which onboard signals actually predict good final 3D reconstruction quality.
What will be your role?
You'll get hands-on experience combining recent advances in 3D vision, vision-language models, and active decision-making, working alongside researchers who build and study these systems daily.
In practice, you'll work with a drone (in simulation), fast 3D foundation models that turn incoming camera images into rough scene geometry in near real-time, and VLMs to analyze scenes for objects of interests. You'll design a coverage-planning strategy that decides where the drone should fly next, and extend it so the drone can recognize user-specified objects using open-vocabulary vision-language models and prioritize extra views around them. Day to day, this involves coding, running flight experiments, and iterating on which signals (angular coverage, view diversity, detection confidence) actually predict good reconstruction quality — with room to adjust scope and direction as the work develops.
This contributes to TNO's broader research on active perception and autonomous 3D scanning, and you'll build hands-on experience with 3D foundation models, vision-language grounding, and the practical challenge of connecting real-time perception to real-time decisions.
What we expect from you
This internship suits a student in a Master's programme like Artificial Intelligence, Computer Science, Robotics, or a related technical field, with a solid foundation in computer vision and machine learning. We're looking for someone ambitious and self-driven, comfortable working on an open research problem and motivated by the possibility of turning strong results into a publication. Strong Python skills are important, and experience with 3D vision (point clouds, depth, camera geometry), vision-language models, or robotics/simulation tools is a real plus, though not something you need to arrive already fluent in. What matters most is curiosity and a hands-on, iterative working style: someone who enjoys experimenting and figuring things out rather than expecting a fixed recipe. You'll fit well in our team if you like working independently while staying engaged in regular discussion and feedback with your supervisors. The internship typically runs 6–9 months, in line with a Master's thesis, with some flexibility in timing and structure. Throughout, there's room to grow your skills in 3D vision, vision-language grounding, and active perception research, and if the results are strong enough, we'll actively support you in shaping them into a publication.
We ask you to include the following information in your application:
- Whether you are looking for a graduation project.
- Your preferred duration (6-12 months).
- Your preferred start date (please note that a security screening may affect the earliest possible start date).
What you'll get in return
An internship at TNO means working in an environment where substance and impact are central. You will become part of a knowledge organisation where research and practice come together, and where experts collaborate on solutions to current societal and technological challenges.
Your internship is a period in which you can discover what suits you, where your strengths lie and what you would like to learn next. You are part of a professional working environment, gain insight into how things work in practice, and have the opportunity to build experience that goes beyond this internship alone. For many students, an internship is therefore also a first step in discovering whether TNO could be a potential next step after graduation.
In addition, we offer you:
- A professional and innovative internship environment in which you actively contribute to societal and technological challenges, working alongside leading experts in your field.
- Personal and dedicated supervision, with focus on your learning objectives, development and study assignment.
- Room to develop: you gain relevant work experience, develop both your subject‑specific and professional skills, and build a valuable network.
- Use of a laptop and the facilities you need to perform your work effectively.
- A monthly internship allowance of €615 for a full-time internship, for MSc, BSc and vocational education (MBO) students.
- Up to eight hours of leave per internship month for a full-time internship, allowing you to balance your internship with your studies and personal life.
- A contribution towards travel expenses if you are not entitled to a student travel card.
- A free membership to Jong TNO: the network for young colleagues, where you can meet other TNO colleagues and participate in sports activities, professional and personal development activities, and social events such as the annual ski trip.
TNO as an employer
Our people are at the heart of TNO. Their curiosity, expertise and entrepreneurial mindset make it possible to deliver high-impact research and innovations that contribute to society’s sustainable wellbeing and prosperity. That is why we invest in an inspiring and inclusive working environment where colleagues can excel, have autonomy and continue to grow.
Your talent and ambition have every opportunity to flourish at TNO. You work with experts (both within and beyond TNO), have access to advanced technology and the freedom to explore, experiment and innovate. Our strength lies in independence, reliability and collaboration. We find each other in wonder and ingenuity. We are driven to push boundaries. By working with businesses and government, and by connecting different perspectives, we strengthen our innovative capability and create responsible, meaningful results.
At TNO, we believe this is our time to help society, government and business move forward faster. Together with driven colleagues, you turn knowledge into concrete innovations or ventures that truly make a difference by combining the power of science and entrepreneurship. And in doing so, you make your mark on our time.
The selection process
You can apply for this internship position until the 1st of October, 2026. After submitting your application, you will receive a confirmation by email.
TNO will arrange an appropriate internship agreement. If you have any questions about the content of the internship or the application procedure, you can contact the person listed below.
If you start an internship with us, we will also ask you to provide a Certificate of Conduct (VOG).
For this internship vacancy it is required that the AIVD issues a security clearance (VGB) following a security screening. In any case, please note that this process has an average duration of approximately 8 weeks. If you have been abroad for more than 6 consecutive months, or if you do not have the Dutch nationality, this process may take longer. For more information, please visit the AIVD website.
Important to know before applying:
- Before the start of the internship, an internship agreement must be signed. For students enrolled at a Dutch university or university of applied sciences, TNO uses the UNL-template , supplemented with several TNO‑specific agreements. For students from foreign educational institutions and MBO (secondary vocational education) programmes, the TNO internship agreement applies. TNO does not sign any other internship agreements.
- Before the start of the internship, the educational institution will need to confirm in writing that:
- you are enrolled at the educational institution for the duration of the internship, and;
- the internship forms part of your study programme.
The confirmation of educational institution takes place by signing the UNL template or forms prepared by TNO.
- Interns at TNO must have a registered residential address in the Netherlands at the start of the internship. Carrying out internship activities from abroad is not possible.
- Are you an international student? Please note that you must have a BSN (Dutch citizen service number) before the start of your internship. Applying for a BSN can take several weeks, so make sure to start this process well in advance.
Has this job opening sparked your interest?
Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.