PhD Fellowship: Real-Time Visual AI & Graphics

University of Copenhagen; København; On-site; DKK 323,000 - 387,000; Full time

Job summary

The Department of Computer Science at the University of Copenhagen invites applications for a PhD fellowship in Real-Time Visual Computing and AI (REVCAI). The project aims to develop new algorithms for fast, scalable visual intelligence under practical computational constraints.

Candidates will work within the IMAGE section, collaborating with national and international partners, and may focus on 3D reconstruction, efficient rendering, and high-performance machine learning.

Qualifications

• Strong academic background in CS, computer engineering, robotics, or applied mathematics.
• Strong programming and algorithmic problem-solving skills.
• Experience with graphics, vision, ML, HPC, robotics, or related quantitative methods.
• Experience with Python and/or C++.
• Good English written and spoken skills.

Responsibilities

• Carry through an independent research project under supervision.
• Complete PhD courses corresponding to approximately 30 ECTS / ½ FTE.
• Participate actively in research environments, including a stay at another research institution, preferably abroad.
• Participate in teaching and knowledge-dissemination activities.
• Write scientific papers aimed at leading international conferences and journals.
• Write and defend a PhD thesis on the basis of the project.

Skills

Programming skills

Python

C++

Graphics

Computer vision

Machine learning

High-performance computing

Robotics

Geometry processing

Optimization

English proficiency

Education

Master's degree in Computer Science / Computer Engineering / Robotics / Applied Mathematics or related field

Job description

The Department of Computer Science at the University of Copenhagen invites applications for a PhD fellowship in Real-Time Visual Computing and AI (REVCAI). The project aims to develop new algorithms for fast, scalable visual intelligence under practical computational constraints.

Candidates will work within the IMAGE section, collaborating with national and international partners, and may focus on 3D reconstruction, efficient rendering, and high-performance machine learning.