PhD Position F/M PhD Position Computer Vision / Deep Learning: Video Generation

Inria; Valbonne; Hybrid; EUR 23,000 - 27,000; Full time

Benefits offered by this job

Transport reimbursement

7 weeks leave + RTT

Teleworking possible

Equipment provided

Social events

Training access

Mutual insurance

Job summary

Inria, au sein de l'équipe STARS, recherche un doctorant pour travailler sur la génération de vidéos synthétiques pour l'apprentissage visuel automatisé. Le stage se déroulera sous la supervision d'Antitza Dantcheva et couvrira des axes autour de la génération contrôlable, de l'apprentissage à partir de données synthétiques et de la détection des deepfakes.

Profil: Master en informatique ou équivalent, solides bases en vision par ordinateur et en mathématiques, programmation en Python et

Qualifications

• Master en informatique ou diplôme équivalent à la date de début.
• Bonnes bases en vision par ordinateur, mathématiques et programmation.

Responsibilities

• Conduire des recherches sur Generating Synthetic Videos for Automated Visual Learning sous la supervision d'Antitza Dantcheva.
• Participer à l'axe: vidéos synthétiques contrôlables et apprenants par données synthétiques.
• Contribuer à la détection et coévolution génération/détection de contenus synthétiques.

Skills

Computer vision

Deep learning

Machine learning

Education

Master degree in Computer Science or related

Tools

Python

OpenCV

PyTorch

TensorFlow

Job description

Fonction : Doctorant

Inria is the French National Institute for Research in Digital Science, of which the Inria Côte d'Azur University Center is a part. With strong expertise in computer science and applied mathematics, the research projects of the Inria Côte d'Azur University Center cover all aspects of digital science and technology and generate innovation. Based mainly in Sophia Antipolis, but also in Nice and Montpellier, it brings together 47 research teams and nine support services. It is active in the fields of artificial intelligence, data science, IT system security, robotics, network engineering, natural risk prevention, ecological transition, digital biology, computational neuroscience, health data, and more. The Inria Center at Université Côte d'Azur is a major player in terms of scientific excellence, thanks to the results it has achieved and its collaborations at both European and international level.

Inria, the French National Institute for computer science and applied mathematics, promotes “scientific excellence for technology transfer and society”. Graduates from the world’s top universities, Inria's 2,700 employees rise to the challenges of digital sciences. With its open, agile model, Inria is able to explore original approaches with its partners in industry and academia and provide an efficient response to the multidisciplinary and application challenges of the digital transformation. Inria is the source of many innovations that add value and create jobs.

Team

The STARS research team combines advanced theory with cutting edge practice focusing on cognitive vision systems.

The Inria STARS team is seeking for a Ph.D. researcher with strong background in computer vision, deep learning and machine learning.

The candidate is expected to conduct researchwith the topic “Generating Synthetic Videos for Automated Visual Learning”, supervised by Antitza Dantcheva in the STARS team, with three axes:

• controllable and generalizable human-centric video generation,
• learning from synthetic data (self-supervised and continual learning), and
• detection of generated videos and deepfakes in a joint generation/detection setting.

Context:

Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding, yet modern deep learning models remain critically dependent on massive amounts of annotated data, whose collection, annotation and curation are costly, time-consuming and increasingly constrained by privacy regulations such as GDPR. This dependency is now one of the main bottlenecks to building robust and generalizable visual learning systems. At the same time, generative models (GANs, diffusion models) have reached a level of realism that makes it possible to synthesize human-centric videos with controllable expressions, gaze, motion and interactions. This thesis explores the foundations of synthetic video generation for automated visual learning: designing new learning paradigms in which synthetic data is generated dynamically to enrich and optimize training sets, with a focus on human-centered tasks (facial expressions, body motion, interaction modeling) and on the joint, co-evolutionary study of generation and detection of synthetic media and deepfakes.

Candidates must hold a Master degree or equivalent in Computer Science or a closely related discipline by the start date.

The candidate must be grounded in the basics of computer vision, have solid mathematical and programming skills.

Preferably in Python, OpenCV, deep learning framework Pytorch or Tensorflow.

The candidate must be committed to scientific research and strong publications.

Avantages

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Contribution to mutual insurance (subject to conditions)