PhD Project in Real-Time Visual Computing and AI Full-time NEW

PhD Fellowship In Real-Time Visual Computing And AI (REVCAI)

The Department of Computer Science invites applicants for a PhD fellowship in Real-Time Visual Computing and AI (REVCAI).

REVCAI investigates how advances in visual computing and artificial intelligence can be translated into systems that are not only accurate, but also fast, efficient, scalable, responsive, and practical to deploy. Modern AI systems have made remarkable progress in understanding and generating visual information, but their computational requirements, latency, limited adaptability, and dependence on large-scale computing infrastructure remain major obstacles to their use in interactive and real-world settings.

The project will develop new algorithms and computational methods at the intersection of computer graphics, computer vision, machine learning, geometry, and high-performance computing. Particular emphasis will be placed on representations and algorithms that make sophisticated visual intelligence possible under practical computational constraints.

The expected start date is March 1, 2027, or as soon as possible thereafter.

The Project

The PhD project will investigate fundamental problems in real-time and resource-efficient visual computing and AI. The precise research direction will be developed together with the successful candidate and may build on their particular strengths and interests.

Potential research directions include real-time 3D reconstruction and representation, neural and point-based representations, efficient rendering and visualisation, high-performance computer vision, efficient machine learning, dynamic and multimodal scene understanding, geometric and physical reasoning, and visual perception for interactive or embodied systems.

A central theme of the project is that computational efficiency is not merely an implementation detail. Latency, memory consumption, scalability, and computational cost can fundamentally determine whether an algorithm can be used in an interactive system, on resource-constrained hardware, or as part of a larger perception-and-action loop. The project will therefore investigate algorithmic and representational choices that improve computational performance while retaining — or improving — accuracy, robustness, and generalisation.

The project may address questions such as:

• How can complex visual and multimodal information be represented and processed at interactive or real-time rates?
• How can modern visual AI methods be made substantially more computationally efficient and scalable?
• Which representations best combine appearance, geometry, semantics, dynamics, and physical information?
• How can visual representations be designed not only for reconstruction or prediction, but also for interaction and decision-making?
• How should visual computing systems be evaluated when latency, memory, computational resources, robustness, and adaptability matter alongside conventional accuracy measures?

Depending on the research direction, the work may range from low-level GPU and systems optimisation to the design of new representations, learning algorithms, or complete real-time visual computing systems. Applications may include robotics and autonomous systems, interactive 3D applications, augmented and virtual reality, scientific and biomedical imaging, and other domains in which visual information must be processed efficiently and reliably.

The successful candidate will be expected to develop novel methods, implement and experimentally evaluate them, and compare them against relevant state-of-the-art approaches. We are particularly interested in research that combines strong algorithmic ideas with convincing practical demonstrations and careful empirical evaluation.

We are looking for candidates within the fields of Computer Science, Computer Engineering, Robotics, Applied Mathematics, or related areas.

Applicants should have strong technical and analytical skills and an interest in developing high-performance algorithms for visual computing and artificial intelligence. Experience in one or more of the following areas is advantageous:

• computer graphics or computer vision,
• machine learning,
• 3D reconstruction or representation,
• GPU programming or high-performance computing,
• robotics or embodied AI,
• geometry processing,
• scientific computing,
• optimisation or applied mathematics.

Strong programming skills are important. Experience with Python and/or C++ and modern machine-learning or GPU-computing frameworks is particularly relevant.

We do not expect candidates to already be experts in all of these areas. We particularly value curiosity, strong problem-solving ability, mathematical and algorithmic thinking, and an interest in understanding how methods work rather than treating existing models as black boxes.

The project is supervised by Assistant Professor Bernhard Kerbl at the Department of Computer Science, University of Copenhagen.

The candidate will join the IMAGE section at the University of Copenhagen, an active research environment working across computer graphics, computer vision, image analysis, geometry, computational modelling, and artificial intelligence.

The project will provide substantial freedom to develop an independent research profile within the broader REVCAI agenda. The candidate will have opportunities to collaborate with researchers at the University of Copenhagen and with national and international research partners, and to contribute both to scientific publications and to open-source research software.

IMAGE offers a friendly, collaborative, and informal research environment with close interaction between faculty, postdoctoral researchers, and PhD students. We value curiosity, technical depth, openness, and teamwork, and aim to provide a supportive environment in which PhD students can develop into independent researchers.

Principal supervisor: Assistant Professor Bernhard Kerbl, Department of Computer Science E-mail: beke@di.ku.dk Telephone: +436504678319

The PhD Programme

The PhD programme is a three-year full-time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master's degree.

To be eligible for the regular PhD programme, you must have completed a degree programme equivalent to a Danish master's degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. computer science, computer engineering, robotics, applied mathematics, physics, or a related discipline. For information on eligibility of completed programmes, see General assessments for specific countries and the Assessment database.

Employment as a PhD fellow is full-time and for a maximum of three years.

Employment is conditional upon successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The position is covered by the Memorandum on Job Structure for Academic Staff.

Salary, pension, and other conditions of employment are set in accordance with the Agreement between the Ministry of Finance and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 31,800 DKK/approx. 4,200 EUR (August 2026 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18.07% to your pension fund.

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.

We Are Looking For The Following Qualifications

• A strong academic background in computer science, computer engineering, robotics, applied mathematics, physics, or a related field.
• Strong programming and algorithmic problem-solving skills.
• Experience with one or more of computer graphics, computer vision, machine learning, high-performance computing, robotics, geometry processing, optimisation, or related quantitative methods.
• Relevant research, thesis, project, or publication experience.
• Programming experience, preferably in Python and/or C++.
• An interest in computational efficiency and in understanding the algorithmic and systems aspects of modern visual AI.
• A curious and analytical mindset and an ability to work independently as well as collaboratively.
• Good written and spoken English skills.

Application And Assessment Procedure

Your application, including all attachments, must be in English and submitted electronically by clicking Apply for position below.

Please include:

1. Motivation letter (max. one page), describing your motivation for applying and your research interests relevant to the position.
2. Curriculum vitae, including information about your education, experience, language skills, technical skills, and other qualifications relevant to the position.
3. Original diplomas for Bachelor's and Master's degrees and transcripts of records in the original language, including an authorised English translation if issued