UserAccount: Master's thesis: Application of deep learning methods to 3D LiDAR environment data (37053)
UserAccount: Master's thesis: Application of deep learning methods to 3D LiDAR environment data (37053)
Posted on :
09-06-2025
Employer Active
1 Vacancy
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Share
Send me jobs like this
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Job Description
Winter Semester 2025/26 Fixed term for 6 months
YOUR TASKS:
- Develop intelligent algorithms for demanding outdoor applications based on 3D LiDAR data
- Explore state-of-the-art deep learning methods for 2D/3D environment perception (segmentation object detection and classification)
- Train deep learning models and evaluate various algorithms in terms of accuracy and efficiency
- Work with cutting-edge 3D LiDAR sensors and gain hands-on technical experience
- Assess the applicability of deep learning methods on modern AI accelerators such as NVIDIA Jetson and Hailo
- Collaborate closely with engineers to develop innovative solutions
- Document your results in a structured and traceable manner
YOUR PROFILE:
- You are currently pursuing a masters degree in computer science physics electrical engineering mathematics or a related field
- You enjoy diving into new and challenging topics and developing novel solutions
- You have solid programming skills ideally in C or Python
- You have initial experience with deep learning and frameworks such as TensorFlow or PyTorch
- You work in a systematic and structured manner
- Creativity in problem-solving and a passion for innovation round off your profile
Contact:Sarah Disch
Employment Type
Student
Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.
