Doctoral researcher in Computer Vision for Deepfake Detection

About this position

About us...

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Interdisciplinary Centre for Security, Reliability and Trust ( SnT ) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.

We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications.

About the role...

We offer an attractive PhD candidate position in close collaboration with our industrial partner, POST Luxembourg , one of the country's largest employers and a leading provider of postal, telecom, ICT, and financial services.

The successful candidate will join the Computer Vision, Imaging, and Machine Intelligence (CVI²) research group ( CVI² Group ), led by Prof. Djamila Aouada, to pursue a PhD in Computer Vision with a focus on Media Forensics and Deepfake Detection. The candidate will conduct research on predefined topics contributing to SnT's and POST Luxembourg's R&D activities. This position involves conducting full-scale research, from reviewing state-of-the-art methods to implementing and validating tangible solutions and disseminating results.

Key Responsabilities:

• Conduct research on a predefined topic and produce meaningful results
• Disseminate research outcomes through scientific publications and/or patents
• Propose and implement innovative and practical solutions
• Support the setup and execution of experiments
• Participate in proposal writing for research projects
• Contribute to organizing workshops and demonstrations
• Engage in outreach activities to promote SnT's research and citizen science initiatives

Your profile...

• A Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or a related field
• A strong background in image/signal processing, particularly in computer vision.
• Strong programming skills and experience with at least one deep learning framework e.g. TensorFlow or PyTorch
• Familiarity with machine learning and deep learning concepts
• Experience with deep learning for face-related tasks, including face recognition, landmark detection, emotion & expression recognition, and deepfake generation, is an asset
• Solid foundation in applied mathematics
• A particular interest in media forensics and misinformation dynamics
• Ability to adapt and thrive in a fast-paced research environment
• Attributes such as commitment, collaboration, intellectual curiosity, and strong critical thinking
• Fluency in English is required

In return you will get…

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the "University of the Greater Region" (UniGR)
• A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

How to apply...

Applications, written in English should be submitted online and should include:

• Curriculum Vitae
• Publication list, if applicable
• Transcripts of all modules and results from university-level courses taken
• Research statement outlining the candidate's topics of particular interest (approximately 300 words)
• GitHub or GitLab webpage showcasing completed projects in Computer Vision

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.