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

Technische Universität München (Technical University of Munich); München; Vor Ort; EUR 45.000 - 57.000; Vollzeit

Zusammenfassung

The 3D Understanding Group at a leading university is seeking highly motivated PhD students and PostDocs in 3D Machine Learning and Vision. These fully-funded positions offer competitive salaries and the chance to drive innovative research at the intersection of computer vision and machine learning.

Leistungen

Fully funded positions

Benefits according to German public service

Qualifikationen

• PhD applicants must hold a Master’s degree in computer science or equivalent.
• Fluent written and spoken English skills required.
• Experience with deep learning frameworks like TensorFlow or PyTorch.

Aufgaben

• Conduct research in 3D Machine Learning and Vision.
• Develop generative 3D models from visual data.
• Collaborate on machine learning approaches for scene understanding.

Kenntnisse

Fluent English

C++

Deep Learning

Ausbildung

Master’s degree in computer science

Tools

TensorFlow

PyTorch

Jobbeschreibung

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

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

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Wissenschaftliches Personal

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
• 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 ([e-mail])
• Please understand that we cannot review incomplete applications Website: https://angeladai.github.io/openings.html
  
  

24.06.2019, Wissenschaftliches Personal

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 ([e-mail])
• 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 ([e-mail])
• Please understand that we cannot review incomplete applications
  
  

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

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Kontakt: [e-mail]

Mehr Information

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

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