Master Thesis - Unsupervised Learning for Multi-Modal Sensor Fusion in ADAS
Join Zenseact in developing cutting-edge AI for autonomous driving! Work on unsupervised learning to enhance multi-modal sensor data, paving the way for safer, smarter vehicles.
Shape the Future of Autonomous Driving with Us!
Why this matters
At Zenseact, we are pushing the boundaries of Advanced Driver Assistance Systems (ADAS) by developing cutting-edge software that enhances safety and efficiency on the road. ADAS relies on multiple sensors, such as cameras, lidar, and radar, to navigate various driving conditions. This project explores how to leverage large amounts of unlabelled multi-modal data to pre-train encoders, using AI to create more robust sensor data representations. This will improve the accuracy and speed of object detection and other key tasks.
If you are excited about working on unsupervised learning techniques that can influence real-world autonomous driving, we want to hear from you!
Your Role in the Project
In this master thesis project, you will:
- Pre-train encoders using an unsupervised approach for different sensor modalities (e.g., camera, lidar, radar).
- Explore and implement strategies to encourage cross-modal interactions, enhancing the combination of data from multiple sensors.
- Evaluate the performance of these pre-trained encoders on downstream tasks like object detection, comparing their efficiency with traditionally trained encoders.
- Fine-tune the models based on your findings and document the results in technical reports, sharing your insights with a broader audience.
- Collaborate closely with experts and contribute to potential publications, which could be presented at top-tier conferences (e.g., CVPR, ICLR, NeurIPS).
What’s in it for you?
- You’ll work with leading-edge technology, contributing to innovation in a high-impact field like autonomous driving.
- Gain hands-on experience in deep learning, unsupervised learning, and sensor technology.
- Opportunity to publish your work with expert guidance and become a part of the research community.
- Flexible start date to accommodate your academic schedule.
- Networking opportunities with professionals across Zenseact’s global teams and access to mentorship to help shape your career path.
What we’re looking for
We are searching for (one or two) students who are passionate about AI and autonomous driving with the following qualifications:
- Solid foundation in mathematics (e.g., Calculus, Linear Algebra, Probability, Optimization).
- Strong programming skills (e.g., Python, Algorithms, Data Structures).
- Experience in one or more of the following:
- Deep learning (representation learning, unsupervised learning).
- Computer vision.
- Signal or image processing.
- Knowledge of sensor technologies (e.g., lidar, radar, cameras) is a plus.
- Familiarity with Linux and Git.
- Excellent communication and collaboration skills.
How to apply & important details
Please submit individual applications including your CV, motivational letter, and grade transcripts.
- Planned start: January 2025 (flexible).
- Final application date: November 15, 2024 (applications reviewed on a rolling basis).
- Duration: 30 ECTS.
For any questions regarding the project, feel free to contact supervisors: julius.wang@zenseact.com and maria.priisalu@zenseact.com
More about Zenseact
Our software makes a difference.
Using AI-based technology to create the ultimate driver support, we’re fighting to end car accidents and make roads safe for everyone. Around 1,4 million people die in traffic yearly while approximately 50 million people get injured. Many get disabled as a result of their injury. We can do better.
One purpose, one product.
We’re a software company dedicated to revolutionizing car safety. By designing the complete software stack for autonomous driving and advanced driver-assistance systems, we’re fighting to end car accidents and make roads safe for everyone. Zenseact was founded by Volvo Cars, and the teams are based in Gothenburg, Sweden, and Shanghai, China.When we aim for zero accidents faster, we strive to speed up the transition to safe automation. This is essentially achieved by making cars updatable – like a computer or a phone. With regular software updates, a vehicle can be made safer long after its production. By accelerating improvement loops, shortening development cycles, and deploying high-capacity software quickly, we can make cars safer, faster.
Culture with people at heart
To achieve our mission of saving lives and ending traffic accidents is to go where nobody has before. It requires us to venture into the unknown, pioneering new technology and pushing the frontier of autonomous driving. While there’s no denying our determination and expertise, we must stand united to succeed. By fostering a culture of support and enablement – a place of psychological safety where all of us can thrive – everything else will follow. We call this a people-at-heart culture. This culture means caring. It means the company cares about me, and we care about one another. It means sharing, so we give each other energy and have fun together. Our culture is also about belonging. It’s important to feel at home and that we can be ourselves at work. Finally, a people-at-heart culture means well-being. So, we enjoy the flexibility needed to be and do our best – at work and in life.
Zenseact works proactively to create a culture of diversity and inclusion, where individual differences are appreciated and respected. To drive innovation we see diversity as an asset, which means we value and respect differences in gender, race, ethnicity, religion or other belief, disability, sexual orientation or age etc.
Interviews are held on a continuous basis, so we highly recommend that you submit your application at your earliest convenience.
- Competence area
- Opportunities for Students, Graduates & Innovators
- Locations
- Gothenburg, Sweden
- Remote status
- Hybrid
Gothenburg, Sweden
About Zenseact
One purpose, one product
We are a software company focused on transforming car safety. By developing a complete software stack for autonomous driving and advanced driver-assistance systems, we aim to eliminate car accidents and make roads safer for all. Founded by Volvo Cars, Zenseact operates globally, with teams in Gothenburg and Lund, Sweden; Munich, Germany; and Shanghai, China.
Master Thesis - Unsupervised Learning for Multi-Modal Sensor Fusion in ADAS
Join Zenseact in developing cutting-edge AI for autonomous driving! Work on unsupervised learning to enhance multi-modal sensor data, paving the way for safer, smarter vehicles.
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