The Visual Computing & Artificial Intelligence Group at the Technical University of Munich invites highly motivated applicants for fully-funded PhD, Intern, and PostDoc positions. These roles focus on cutting-edge research at the intersection of computer vision and machine learning, offering an excellent opportunity to contribute to high-impact studies in 3D vision and graphics.
- 🎓 Fully-funded PhD, intern, and PostDoc positions available at Technical University of Munich.
- 🌐 Focus on computer vision and machine learning, including 3D vision, graphics, and deep learning techniques.
- 🧠 Research areas include 3D reconstruction, semantic scene understanding, and generative models.
- 📚 Required qualifications: Master’s degree, expert coding skills, background in vision/graphics/ML, and strong motivation.
- 📄 Documents needed: CV, research statement, transcripts, and recommendation letters as per guidelines.
Designation
- PhD Students
- Interns
- PostDocs
| Position | Type | Salary/Support | Contract Type |
|---|---|---|---|
| PhD | Full-Time | 45k – 57k Euro/year + benefits | Fixed-term |
| PostDoc | Full-Time | 45k – 57k Euro/year + benefits | Fixed-term |
| Intern | Temporary | Stipend for living expenses | Internship |
Research Area
- Neural Rendering
- Generative AI (Diffusion, GANs, etc.)
- 3D Reconstruction
- SLAM / Pose Tracking
- Semantic Scene Understanding
- Face / Body Tracking
- Non-Linear Optimization
- Media Forensics / Fake News Detection
Location
Technical University of Munich, Germany
Eligibility/Qualification
For PhD Candidates:
- Master’s degree
- Expert-level coding skills
- Background in vision/graphics/ML
- Proficient English skills
- Strong background in numerical optimization
For Interns:
- Ongoing PhD (minimum two years)
- At least one top-tier publication (CVPR, ICCV, ECCV, Siggraph, etc.)
For PostDocs:
- Completed PhD (or very close to completion)
- Strong publication record at top-tier venues (CVPR, ICCV, ECCV, Siggraph, etc.)
Description
The positions involve a flexible research direction with a heavy focus on deep learning techniques, particularly in static and dynamic 3D reconstruction and semantic scene understanding. The goal is to revolutionize research in 3D learning through high-impact contributions.
How to Apply
Interested candidates must submit the following documents:
- Brief CV (one page)
- Short and precise research statement (maximum one page) addressing:
- What concrete problem do you want to solve?
- Why do you want to solve it?
- How do you want to solve it?
- What are your expected final results and general aims?
- Relevant references (preferably papers authored by you)
- Bachelor’s and Master’s transcripts
- At least two recommendation letters
Follow the specific guidelines for submission provided on the university’s application portal.
Last Date to Apply
Applications are accepted on a rolling basis; prospective candidates are encouraged to apply promptly to secure a position.
