Research Assistant/Associate – Doctoral Candidate (f/m/d) – Evaluation of AI-enhanced Image and Video

Weitere Informationen

The successful candidate will be employed under a regular employment contract.
The position is to be filled at the earliest possible date and offered for a fixed term of three years.
It is intended to extend the initial contract period by at least one year.
The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).
This is a full-time position.
The successful candidate has the opportunity to pursue a doctoral degree in this position.
The salary is based on the German public service salary scale (TV-L).
The position corresponds to a pay grade of EG 13 TV-L.

Unser Profil

At the Institute of Communications Engineering, we investigate the interplay between multimedia signal processing, human perception, user experience and the sustainability of communication systems. We primarily analyse audiovisual systems along the entire transmission chain (recording, post-processing, coding, transmission, playback and optimization) to improve their quality and efficiency in operation and development. We consider aspects such as signal quality, perception, user behavior, cognitive performance, quality of experience and resource consumption, from energy to human resources such as fatigue, cognitive load or “cybersickness”. Our interdisciplinary research combines engineering, computer science, human-machine interaction and psychology. We pursue an open science approach for research that is as reproducible as possible and are closely networked with international partners from science and industry as well as spin-offs, for example from Prof. Raake’s predecessor institute at TU Ilmenau.

Artificial intelligence and machine learning processes enable the generation, improvement and efficient processing of image and video signals. This ranges from video streaming with AI-based resolution upscaling (spatially, e.g. to 4K or 8K UHD, or temporally to HFR with 120 fps) and the adjustment of the dynamic range and/or color space, to AI-based encoding and reconstruction and AI-supported generation of video content. To assess the success of traditional image and video processing, prediction models of visual quality are usually used, which provide an estimate of the quality from the user's perspective based on the signal. These methods are trained and validated based on perception tests with test subjects. However, current quality estimation methods can only be used to a very limited extent in the field of AI-supported image and video processing. Without valid quality measures, it is therefore difficult to optimize AI-based processing appropriately.

To close this gap, research into innovative approaches to visual system evaluation is necessary. This includes investigations at the interface between audiovisual systems and visual human signal processing as well as signal-based analysis of image and video information. In a team with other researchers at the institute and with international cooperation partners, a framework of AI-based processing methods is constructed and novel methods for assessing the “visual quality” of AI-based processing as well as prediction models for automatic quality estimation are being developed. A particular challenge here is how AI methods can be used profitably for modeling despite the small amount of data (“ground truth”).

Why you should join us:

• Research opportunity in groundbreaking audiovisual and immersive technologies.
• Access to advanced research infrastructure.
• A collaborative research environment.
• A research institute in dynamic development.
• The opportunity to contribute to the development of the next generation of multimedia technologies and methods for evaluating their perception.

Ihr Profil

• Very good University degree (Master’s degree or equivalent) in electrical engineering, computer engineering, computer science, cognitive science or a related field.
• Passion for the interface of communication systems, human perception and signal processing as well as perception-based system optimization.
• Experience in machine learning techniques.
• Programming skills (Python or C++/C#).
• Strong interest in interdisciplinary collaboration.

Ihre Aufgaben

• Cooperative development of a research framework of current AI-based image and video processing methods as “systems under test”.
• Research into novel test procedures for the visual evaluation of AI-supported image and video processing.
• Research into novel signal- and bitstream-based methods for modeling the visual perception and evaluation of AI-supported image and video processing.
• Participation in international standardization (e.g. International Telecommunication Union - ITU-T, Video Quality Experts Group - VQEG).
• Collaboration in an interdisciplinary and international research environment.

Über uns

RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung.

Besoldung / Entgelt

EG 13 TV-L