Internship | Test-Time Adaptation for Robust AI

Make your mark on our time? Be an intern at TNO!

About this position

Do you want to contribute meaningfully to our AI research by applying Test-Time Adaptation to help robots and drones tackle challenging situations more intelligently?

Recently, a new paradigm emerged in the Machine Learning (ML) research field called Test-Time Adaptation (TTA). TTA is a generically applicable technique to make pre-trained ML models adapt to the situation or environment of a system during operations or test-time. The direct impact of this research is that a autonomously driving vehicle with mud on its sensors would still detect obstacles on its path with an adaptive model where a non-adaptive model would fail. The adaptation process happens continuously. A key challenge is to extract knowledge from the situation during test-time without any semantic meaning supplied by humans.

What will be your role?

The Test-Time Adaptation concept has existed now for several years. In this time the state-of-the-art has moved fast in different directions. One of those is the adaptation of a model on as little data as possible whilst optimizing for performance gain. Another direction is adaptation with little extra computational resources on cheap hardware. Stability of the adaptation process is another hotly researched direction. Stability guarantees are difficult to verify and controlling stability is a key challenge in TTA.

The extraction of knowledge from raw data brings additional challenges, such as the optimal use of the available information, control and stability of the adaptation process and the optimal use of compute resources associated with these extra functionalities.

In this assignment you will tackle one or more of these research directions and challenges in your applied research. You will work with state-of-the-art ML techniques and implement and evaluate those in military-relevant scenarios. The applications of your research are numerous and you can decide which to pick. We expect you to perform a critical analysis of the limitations of current methods and that you propose new, improved or extended methods to bring the TTA field one step further.

Your thesis project will be part of the Collaborative Autonomous Systems department within TNO. This department is a dynamic and interdisciplinary team of approximately 35 experts working on advanced autonomy and AI solutions for ground, air and maritime systems. The department has strong expertise in mission autonomy, localization and navigation, situational awareness and robotics.

What we expect from you

We are looking for a motivated master’s degree student with an interest in Machine Learning and Deep Learning for defence related applications. This position is a great fit for students who enjoy combining theoretical concepts with hands-on experiments and applications.

Requirements:

• You are in the last phase of your master’s degree in the fields (or a field related to): Artificial Intelligence, Computer Science, Robotics, Electrical Engineering, Applied Mathematics or Physics.
• A background in Machine Learning and Deep Learning.
• Experience with programming and perception algorithms.
• Interest in adaptive and continuously learning algorithms.

The duration of this thesis project is between 9 to 12 months.

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.

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.

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.