Internship | Development of a Context-Aware AI Driver Assistant

StudentJob; Helmond; On-site; EUR 6,000 - 7,000; Part time

Benefits offered by this job

€615 monthly internship allowance (MSc

Travel expense contribution

Jong TNO membership

Job summary

TNO invites motivated HBO or Master’s students to join the MARQ Digital Lab for an internship focused on building a context-aware AI driver assistant. You will design software architecture to connect a driving simulator (SCANeR) with a locally hosted LLM on MARQ Lab GPUs, study real-time context updates, and evaluate open-source LLM options for safe, timely driver support.

The project aims to deliver a working proof-of-concept, integrating with multiple simulation platforms and providing

Qualifications

• Able to integrate with driving simulator software using C++ and Python.
• Knowledge of AI/ML, LLMs, and prompt engineering for real-time context handling.
• Experience with REST APIs, Linux basics, Docker, and Git.
• Familiarity with ROS 2, Kubernetes, or GPU computing is an advantage.
• Interest in automated driving (ADAS/CCAM) and Human-AI Interaction.

Responsibilities

• Develop a context-aware AI driver assistant for driving simulations.
• Architect system integration between SCANeR and a locally hosted LLM on MARQ Lab GPUs.
• Explore data/context update frequencies for real-time interaction.
• Evaluate open-source LLM suitability for context-aware driver assistance.
• Produce a proof-of-concept and perform system performance evaluations.

Skills

C++

Python

AI/ML knowledge

LLMs & prompt engineering

REST APIs

Linux

Docker

Git

ROS 2

Kubernetes

GPU computing

Interest in ADAS/CCAM

Education

Enrollment in HBO or Master’s program

Tools

Docker

Git

ROS 2

Kubernetes

GPU computing

Job description

About this position

Within the MARQ Digital Lab, you will develop a context-aware AI assistant for a driving simulator. The assistant will leverage a Large Language Model (LLM) that receives real-time contextual information from the simulation, including the road environment, traffic situation, vehicle status, and driver behavior (e.g., eye tracking and driver inputs such as steering, throttle, and braking). Based on this information, the AI assistant should be able to answer driver questions and proactively provide warnings, explanations, and driving advice.

You will design and implement a software architecture that connects the driving simulator (SCANeR) to a locally hosted LLM running on the GPU infrastructure of the MARQ Digital Lab. The project will investigate how simulation context can be efficiently supplied to the LLM, determine the update frequency required for real-time interaction, and evaluate which open-source LLM is best suited for this application.

The final result will be a working proof-of-concept of an AI-powered driver assistant that combines natural language interaction with context-aware support during driving simulations. The solution will serve as a foundation for future research into AI-assisted driver coaching, Human-AI Interaction, and the validation of ADAS and CCAM systems within the MARQ Digital Lab.

What will be your role?

Possible Research Questions

• How can simulation context be efficiently provided to an LLM in real time?
• Which open-source LLM is most suitable for a context-aware driver assistant?
• What system architecture and context update frequency are required for natural and timely interaction?
• How can an AI assistant effectively support drivers without becoming distracting?

Expected Deliverables

• A working proof-of-concept of a context-aware AI driver assistant.
• Integration with at least one simulation platform (SCANeR, and optionally CARLA or NVIDIA Isaac Sim).
• A locally hosted LLM running on the GPU infrastructure of the MARQ Digital Lab.
• An evaluation of system performance, latency, and applicability for research and validation of ADAS and CCAM systems.

What we expect from you

• C++ for integration with driving simulator software.
• Python for AI integration, rapid prototyping, and API development.
• Knowledge of Artificial Intelligence (AI) and Machine Learning.
• Familiarity with Large Language Models (LLMs) and prompt engineering.
• Experience with REST APIs or other communication mechanisms.
• Basic knowledge of Linux, Docker, and Git.
• Interest in automated driving (ADAS/CCAM), simulation, and Human-AI Interaction.
• Experience with ROS 2, Kubernetes, or GPU computing is considered an advantage but is not required.

This internship is suitable for both HBO and Master's students. For a Master's project, additional emphasis can be placed on system architecture, AI evaluation, explainable AI, and research into the effectiveness of context-aware driver assistance in advanced simulation environments.

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