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Internship | Active Inference for Statistical Model Checking on Radar Systems

Geplaatst 26 mrt. 2024
Werkervaring
0 tot 1 jaar
Full-time / part-time
Full-time
Soort opleiding
Taalvereiste
Engels (Vloeiend)

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Internship | Active Inference for Statistical Model Checking on Radar Systems

Den Haag

Fulltime

Verifying robustness of signal processing chains is of high importance. The project investigates how learning techniques, e.g., active inference or machine learning, can decrease the computational overhead of counter example generation.

WHAT WILL BE YOUR ROLE?

Future generation radar systems should operate with a high degree of autonomy. More specifically, these systems should be able to adapt and react on unknown or unforeseen conditions with limited human intervention. The required enabling technologies to guarantee safe operation can develop quickly when conventional adaptive, control, and decision making techniques will be combined with the rapid innovations in artificial intelligence (AI). Similar trends have been seen in novel self-driving algorithms for the automotive industry.

This project is an interdisciplinary MSc internship and/or MSc thesis to combine learning algorithms with statistical model checking (SMC) into the domain of signal processing of radar systems. For radar systems, it is important to understand which input scenarios, e.g., combination of target, weather, and environmental conditions, may lead to performance degradation or, even worse, to failure. Generating counter examples is essential in order to understand the potential shortcomings of a radar signal processing chain. However, the number of input scenarios can be enormous and applying extensive statistical model checking to each input scenario will become infeasible. The idea is to apply state-of-the-art learning techniques (AIs) to learn and adapt the input sampling space on-the-fly in order to reduce the total number of samples required to obtain an reliable counter example. In other words, can active inference, machine, reinforcement, or other learning techniques be applied to SMC to sample the input scenarios in a ‘smart’ way?

You will perform this assignment in the Department of Radar Technology. We are a passionate and creative group of professionals (60 people) dedicated to the specification, development and evaluation of innovative, high-performance MMICs, miniaturised and integrated RF subsystems, antennas and front-ends, and signal processing algorithms. The department is at the heart of novel, game-changing radar system and signal processing concepts for the military, space and civil domains.

HOW DO YOU WANT TO CONTRIBUTE TO TOMORROW'S WORLD? HOW BIG CAN YOUR IMPACT BE? COME AND WORK AT TNO AND ENVISION IT.

WHAT WE EXPECT FROM YOU

You are in the final stages of your MSc degree in artificial intelligence, computer science, systems and control engineering, physics, mathematics, electrical engineering, or a similar degree. You have experience in programming in Matlab, Python and/or related language, you are quick in understanding new software, and you are pragmatic and focused on making things work. Next to technical expertise, we value communication skills and a results-driven attitude.

WHAT YOU’LL GET IN RETURN

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

Innovation with purpose: that is what TNO stands for. We develop knowledge not for its own sake, but for practical application. TNO connects people and knowledge to create innovations that boost the competitive strength of industry and the well-being of society in a sustainable way.

Management Consulting
Den Haag
3.300 medewerkers

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