Assistant/Associate Professor in multimodal generative AI models for audio - permanent contract

Télécom Paris; France; Sur place; EUR 40 000 - 70 000; Plein temps

Résumé du poste

A leading multidisciplinary research center in France is seeking a Researcher in generative AI to join its dynamic team. In this role, you will design teaching programs, conduct advanced research, and foster collaborations. The ideal candidate will hold a PhD and possess exceptional skills in machine learning and generative AI techniques. The position offers engaging work in a cutting-edge field, along with benefits including flexible remote work and extensive paid leave.

Prestations

1 to 3 days of remote working

49 days of paid leave/RTT

Mutual insurance & provident fund

Qualifications

• You must have a PhD and be fluent in English.
• Expertise in machine learning, particularly in generative AI.

Responsabilités

• Participate in the design and implementation of teaching programs.
• Conduct research in your scientific field.
• Develop partnerships and collaborations in your field.

Connaissances

Generative AI (diffusion model, score/flow matching, tokenization, disentanglement)

Statistical learning and advanced deep learning

Interpretability and explainability of generative models

Ethical and societal considerations

Fluent in English

Formation

PhD

Description du poste

Organisation/Company Télécom Paris Research Field Technology Other All Computer science Mathematics Researcher Profile Recognised Researcher (R2) Positions Research Support Positions Country France Application Deadline 15 Mar 2026 - 00:00 (Europe/Paris) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Télécom Paris, an international multidisciplinary center for education, research, and innovation, is a leader in the digital world.

The number of methodological challenges raised by the application of Generative-AI approaches to audio data (speech, music, environmental sounds) is considerable. While advances in recent years have largely relied on pattern recognition models and optimization techniques to scale up, the emergence of generative models—whether based on diffusion models (score/flow matching) or autoregressive approaches—is now opening up new perspectives, while raising fundamental scientific questions.

The extreme complexity and diversity of audio data (multilingual speech, rich and varied musical signals, complex acoustic environments, biased or noisy data), combined with the growing demands of these applications (interpretability, reliability, robustness, fairness, near–real-time generation, control over style or generated content, etc.), make it necessary to rethink existing methodological and theoretical frameworks. These challenges take on an additional dimension with the development of multimodal generation, where audio is produced from heterogeneous modalities (e.g., text to audio, image to audio, or even video to audio), sensory modalities (brain to audio), or biological sensors (sweating, ECG, etc.). These scenarios raise new scientific challenges, both in terms of modeling (intermodal alignment, joint representation, generation control) and in terms of usage (perceptual quality, semiotic consistency, acceptability).

Your main tasks will be to:

• Participate in the design and implementation of teaching programs in your scientific field
• Conduct research in your scientific field
• Participate in the development of partnerships, collaborations and contractual relationships in your scientific field

To succeed in this role, you have a PhD and you are fluent in English.

The position is open to all candidates working in marchine learning, expertise in the following areas will be preferred:

• Generative AI (diffusion model, score/flow matching, tokenization, disentanglement)
• Statistical learning and advanced deep learning (large-scale training, generation control, self-supervised methods, and contrastive learning)
• Interpretability and explainability of generative models
• Ethical and societal considerations: responsible use, audio deepfakes, cultural biases
• Scientific excellence:Renowned laboratories (LTCI, i3, CREST), cutting‑edge equipment, and international recognition.
• Multidisciplinarity: Working at the intersection of all areas of digital technology.
• Personalized support: Integration program, dedicated training, exchange seminars, and paid study trips.
• Benefits: 1 to 3 days of remote working and nomadic working possible, 49 days of paid leave/RTT, mutual insurance & provident fund, etc.

To apply, please send your file before March 15, 2026:

• Detailed curriculum vitae (max 2 pages)
• Covering letter
• Activity report (table of activities) on research (supervision, problems, etc.), eaching (title, volume, etc.) and collective tasks (max 4 pages)
• Teaching description (summary of activities, a brief plan for integration into teaching at university and continuing education) (max 4 pages)
• Research description (summary and results of activities, a brief plan for integration into research) (max 4 pages)
• Copy of the 3 best publications, list of publications
• Names and contact details of 2 qualified references

The selection process takes place in 4 steps:

• Exchange with the host team to establish a list of shortlisted candidate
• Preliminary interview with Human Resources
• Hearing by the recruitment committee and ranking of the selected candidates
• Final interview with the Director of Télécom Paris

Our recruitment is based on skills, without distinction of origin, age, gender identity, or sexual orientation, and all our positions are open to individuals with disabilities.