PhD and PostDoc Positions in 3D Machine Learning / 3D Vision (Dr. Dai) bei Technische Universität München

The 3D Understanding Group at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine learning, and computer graphics. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k – 57k Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D observations. Generating 3D Models From Visual Data: Imagine creating 3D photos, holograms, or your own custom video game content from a quick video observation. We develop generative 3D models from 2D or 3D observations, focusing on indoor environments. Qualifications: • Applicants for a PhD must hold a Master’s degree in computer science or equivalent • Fluent written and spoken English skills • Proficient C++ coding skills • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) • Enthusiasm and self-drive towards driving research forward :) How to Apply: • Required Documents: CV, research statement, BA/MA transcripts, (optionally, MA thesis) • Ask two recommenders who know your work to directly email recommendation letters • Send all documents (including rec. letters) directly to Dr. Dai (angela.dai@tum.de) • Please understand that we cannot review incomplete applications Website: https://angeladai.github.io/openings.html

3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D observations.

Generating 3D Models From Visual Data: Imagine creating 3D photos, holograms, or your own custom video game content from a quick video observation. We develop generative 3D models from 2D or 3D observations, focusing on indoor environments.

Qualifications: • Applicants for a PhD must hold a Master’s degree in computer science or equivalent • Fluent written and spoken English skills • Proficient C++ coding skills • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) • Enthusiasm and self-drive towards driving research forward :) How to Apply: • Required Documents: CV, research statement, BA/MA transcripts, (optionally, MA thesis) • Ask two recommenders who know your work to directly email recommendation letters • Send all documents (including rec. letters) directly to Dr. Dai (angela.dai@tum.de) • Please understand that we cannot review incomplete applications

Website: https://angeladai.github.io/openings.html

Kontakt: angela.dai@tum.de