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Djamila Aouada

Professor at University of Luxembourg

University of Luxembourg

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Luxembourg

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Research Interests

Statistics

10%

Artificial Intelligence

20%

Applied Mathematic

20%

Computer Vision

20%

Electrical Engineering

20%

Mathematics

20%

Computer Science

20%

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Positions2

Publisher
source

Djamila Aouada

University Name
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University of Luxembourg

Doctoral Researcher in Computer Vision for Deepfake Detection

The University of Luxembourg, a leading international research university, offers a PhD position in Computer Vision for Deepfake Detection within the Interdisciplinary Centre for Security, Reliability and Trust (SnT). The successful candidate will join the Computer Vision, Imaging, and Machine Intelligence (CVI²) research group, led by Professor Djamila Aouada, and collaborate closely with POST Luxembourg, a major industrial partner. This research opportunity focuses on media forensics and the detection of deepfakes, contributing to both academic and industry-driven R&D activities. As a doctoral researcher, you will conduct full-scale research, including reviewing state-of-the-art methods, implementing and validating solutions, and disseminating results through scientific publications and patents. Responsibilities also include supporting experiments, proposal writing, organizing workshops and demonstrations, and engaging in outreach activities to promote SnT's research and citizen science initiatives. Applicants must have a Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or a related field, with a strong background in image and signal processing, particularly in computer vision. Essential skills include programming proficiency and experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with machine learning and deep learning concepts is required, and experience with face-related tasks (face recognition, landmark detection, emotion and expression recognition, deepfake generation) is an asset. A solid foundation in applied mathematics and a keen interest in media forensics and misinformation dynamics are important. Candidates should demonstrate adaptability, commitment, collaboration, intellectual curiosity, strong critical thinking, and fluency in English. The University of Luxembourg provides a modern, dynamic, and international environment, with staff from over 90 countries and close ties to the business world and Luxembourg's labor market. The institution offers high-quality equipment, excellent infrastructure, and partnerships with European institutions, innovative companies, and various non-academic partners. Applications must be submitted online in English and should include a CV, publication list (if applicable), transcripts, a research statement outlining topics of interest (approx. 300 words), and a GitHub or GitLab webpage showcasing completed projects in Computer Vision. Early application is highly encouraged, as applications are processed upon reception. The University promotes an inclusive culture and encourages applications from individuals of all backgrounds, upholding equality and respect for employees and students. For further details and to apply, visit the provided application link. Please note that applications by email will not be considered.

Publisher
source

Djamila Aouada

University Name
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University of Luxembourg

Postdoctoral Researcher in Computer Vision

The University of Luxembourg, a leading international research university, is seeking a Postdoctoral Researcher in Computer Vision to join the Computer Vision, Machine Intelligence and Imaging (CVI2) research group led by Professor Djamila Aouada. The university is renowned for its multilingual and interdisciplinary environment, and the Interdisciplinary Centre for Security, Reliability and Trust (SnT) is a hub for innovation in secure, reliable, and trustworthy ICT systems and services. The CVI2 group focuses on advanced research in Artificial Intelligence, with a primary emphasis on Computer Vision, pattern recognition, and visual generative modeling. The group offers opportunities to contribute to diverse projects, including collaborations with industrial partners and academic initiatives at both national and international levels. Research topics include 3D understanding and generation, media forensics, anomaly detection, multimodal learning (especially vision-language models), and computer vision applications for space. Facilities include the Computer Vision Lab, equipped with state-of-the-art visual sensors and acquisition systems, and the Zero-G Lab, which emulates space-like conditions for proximity operations. High-performance GPU computing resources are available to support the design and training of advanced AI models. The research agenda spans the full lifecycle, from data acquisition and preprocessing to model training, validation, and performance evaluation. Key responsibilities for the postdoctoral researcher include shaping research directions, attracting funding in cooperation with industrial partners, contributing to competitive research proposals, coordinating projects, disseminating results through publications in top AI venues, guiding PhD and MSc students, contributing to teaching and seminars, designing large-scale experimental pipelines, developing real-time AI solutions, and participating in outreach activities. Applicants must have a PhD in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related field, with a strong research track record and publications in leading venues. Essential skills include programming, mathematical foundations (linear algebra, probability, statistics, optimization), experience with machine learning and deep learning, independent and collaborative work abilities, analytical and critical thinking, fluency in English, and scientific writing. The University of Luxembourg offers a modern, dynamic environment with high-quality equipment, close ties to industry and society, and a commitment to inclusivity and equality. The position is based at the Kirchberg Campus and is a fixed-term contract. Applications should be submitted online, including a CV with work experience and publications. Early applications are encouraged, and email submissions will not be considered.