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Karlsruher Institut für Technologie (KIT) in Karlsruhe is seeking a researcher to explore efficient long-context models for computer vision and VLA systems in autonomous driving. You will investigate attention optimization, token reduction, pruning and quantization to scale large models without compromising accuracy and real-time performance.
The role requires a strong academic background, experience with deep learning architectures, and a drive to work independently within an international
For more than one decade the Institute of Measurement and Control Systems (MRT) at KIT has been one of Germany’s leading autonomous driving labs. Its unique advantage is the availability of experimental vehicles with sensors, actuators and a complete software stack for automated urban driving. The existing equipment and experience not only enables continuous cutting-edge research in all areas of autonomous driving, but also a wide range of collaborations with leading industrial partners. Research highlights of the MRT are, among others, the successful participation in autonomous driving competitions as well as the development of highly influential benchmark suites like KITTI and KITScenes.
Large foundation models and vision-language-action models increasingly rely on long context windows to reason over high-resolution images, videos, multi-camera sensor streams, maps, interaction histories and language instructions. However, standard attention mechanisms scale unfavorably with context length, and large models remain difficult to deploy under real-time, memory and energy constraints in autonomous systems. You will investigate efficient long-context models for computer vision and VLA systems and apply it to autonomous driving.
The research will combine attention optimization, token reduction, model pruning and quantization to make large models scalable while preserving accuracy, robustness, and downstream action quality. The research will build on established ideas from Transformers, long-sequence attention, memory-efficient attention, vision transformers, deep compression, and recent VLA systems.
You are a dedicated and creative person with
Engage with topics of societal relevance—in an excellent scientific environment that enables change.
We provide you with a structured onboarding program, a broad spectrum of continuing‑education options, and personalised support, thereby fostering your individual growth.
Take advantage of flexible‑hours schemes, remote‑work options, and a 30‑day annual leave entitlement to achieve an optimal work‑life balance.
The “KIT‑Family+” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent‑child office space, and assistance with caring for relatives.
Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well‑being through fitness classes and mental‑health programmes.
Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicketBW, plus a broad selection of cultural and recreational programmes.
Job location
Karlsruhe (and Eggenstein-Leopoldshafen)
Salary
Salary category 13 TV-L; classification is based on personal and professional qualifications.
Contract duration
3 years
Contact person in line-management
Dr. Martin Lauer
martin.lauer@kit.edu
If you have general questions about the application process, please contact
JuliaBoldt
Personalservice (PSE)
julia.boldt@partner.kit.edu
At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply.Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.
Application up to:2026-11-08
Job posting number:1252/2026