Research Assistant/Associate – Postdoc / Doctoral Candidate (f/m/d) – Data-driven and AI-based Analysis and Signal Processing for Audiovisual Media

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 for an initial period 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) in order 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.

In principle, artificial intelligence (AI) and machine learning enable the generation, improvement and efficient processing of audiovisual content. There are many examples, such as AI-based upscaling (of spatial, e.g. to 4K or 8K UHD, or temporal resolution, e.g., to HFR at 120 fps) and the adjustment of the dynamic range and/or color space, acoustic source separation, AI-based encoding and reconstruction of audio or video signals or AI-supported generation of audio or video content such as cinematographic videos or high-quality volumetric video representations of people. Machine learning and AI-based methods have also become established for quality or aesthetic appeal prediction of audio or image and video signals. However, the acoustic, visual or audiovisual signals resulting from AI-based processing cannot be adequately described purely based on signal quality. Accordingly, automated measurement methods for estimating the perceived quality or aesthetics must be able to accurately predict the perceived characteristics and quality criteria of AI-based processing.

At the interface of AI-based audiovisual media processing and “quality measurement” from a human perspective, there is an intensive need for innovative, data-driven signal analysis and evaluation. Due to the ground-truth data required, comprehensive perception tests are necessary, for which laboratory testing is not sufficiently scalable, considering the effort involved. Here, research into innovative approaches including crowdsourcing offer a complementary solution, as already demonstrated by our research group for the cases of 4K video and image aesthetics. The collected measurement signals, data on the AI-supported audiovisual systems, user data recorded during system usage and data on resource consumption represent a comprehensive research database. Innovative approaches need to be developed to annotate and make the data available following the Institute's “Open Science” / “Reproducible Research” approach, considering requirements of anonymization data privacy. The aim is to build on the methods and research tools previously developed by Prof. Raake’s research group at TU Ilmenau and to expand these towards a systematic, AI-supported research data management, in cooperation with partners from the institute's wide research network and to supplement the approaches with new developments.

Why you should join us:

• Research opportunity in novel audiovisual and immersive technologies.
• Access to advanced research and data processing infrastructure (such as CLAIX-2023, the AixCAVE and the comprehensive user testing and system characterization labs currently under development at the institute).
• A collaborative research environment.
• 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) and, if applicable, a completed PhD in electrical engineering, computer engineering, computer science, data analytics or a related field.
• Passion for topics at the interface of communications engineering and multimedia systems, human perception and signal processing as well as system modeling using machine learning and AI methods.
• Extensive experience in machine learning and AI.
• Comprehensive programming skills (Python or C++/C#).
• Great interest in interdisciplinary collaboration.

Ihre Aufgaben

• Cooperative development of AI-supported research data management for heterogeneous audiovisual signals, system, perception and behavioral data.
• Research into novel test procedures for the laboratory and web-based evaluation of audiovisual systems.
• Research into novel signal- and bitstream-based methods for system and signal analysis.
• 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