Full-time

Saalburg-Ebersdorf | Jena

Software Engineering

Introductory information

This thesis evaluates modern end-to-end 3D reconstruction models for automotive multi-camera systems with non-pinhole camera models. Many learned reconstruction methods are designed around pinhole camera assumptions, while vehicle setups often use fisheye or double-sphere camera models.

The goal is to investigate strategies for adapting or refining such methods for robust camera-to-camera extrinsic calibration. Depending on the achieved results, this thesis may contribute to a scientific publication in computer vision, robotics, or autonomous systems.

Your Role

Evaluate learned 3D reconstruction methods such as MASt3R, VGGT, or MapAnything.

Analyze limitations caused by pinhole camera assumptions.

Investigate adaptation strategies such as perspective crops, ray-based formulations, or post-hoc geometric refinement.

Compare learned reconstruction methods against COLMAP-based calibration.

Evaluate accuracy, robustness, scale consistency, and failure cases on vehicle data.

At a minimum we’d like you to have

Good programming skills in Python.

Interest in deep learning, 3D reconstruction, and camera calibration.

Familiarity with Linux-based development environments.

Basic understanding of camera models or image-based 3D reconstruction.

It’s preferred if you have

First experience with PyTorch or similar deep learning frameworks.

Interest in fisheye, omnidirectional, or double-sphere camera models.

Basic understanding of geometric computer vision.

Motivation to combine learned methods with classical geometric optimization.

About

Are you ready to redefine the future of transportation across all domains? At Spleenlab, we're building the safety backbone for autonomous movement, ensuring people and things can navigate the world with confidence. Our expertise spans self-driving cars, trucks, maritime vessels, UAVs, air taxis, helicopters, and traditional aircraft.

We specialize in creating cutting-edge AI perception software powered by machine learning, specifically designed for safety-critical autonomous systems. This isn't just about code; it's about enabling a safer, more efficient tomorrow across land, air, and sea.

As part of our dynamic and interdisciplinary team, you'll work alongside recognized AI leaders, contribute to groundbreaking projects, and directly influence the next generation of autonomous mobility. If you're an ambitious AI professional eager to make a real difference, we want to hear from you.

Benefits

Work-Life-Balance: Flexible working hours and mobile working options.

Ergonomic Workstations: Equipped with height-adjustable desks and ergonomic office chairs.

Company Events: Regular team events, meet & greets, and an annual Christmas party as integral parts of our company culture.

Free Drinks: Enjoy complimentary coffee, tea, and water to keep you refreshed throughout the day.

Your Next Opportunity Starts Here

At Spleenlab, we don’t just accept difference – we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity. We consider all qualified applicants, in accordance with the legal requirements. If you have a disability or special need that requires accommodation, please let us know.

Please send your CV and accompanying material directly to career@spleenlab.ai