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

Karlstad University; Gif-sur-Yvette; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

A prestigious engineering institution in Île-de-France is seeking an Assistant/Associate Professor in multimodal generative AI models for audio. The role involves conducting cutting-edge research, teaching diverse subjects, and developing innovative programs in the rapidly evolving field of generative AI. Candidates must hold a PhD and demonstrate fluency in English. The position offers a permanent contract with opportunities for remote working, significant paid leave, and additional personal benefits. Enthusiastic individuals are encouraged to apply by March 15, 2026.

Prestations

Up to 3 days of remote working

49 days of paid leave/RTT

Health insurance and provident fund

Qualifications

• PhD and fluent in English required.
• Expertise in machine learning preferred.

Responsabilités

• Participate in design and implementation of teaching programs.
• Conduct research in the field.
• Develop partnerships, collaborations, and contractual relationships.

Connaissances

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

Statistical learning and advanced deep learning (large-scale training, generation control, self-supervised methods, contrastive learning)

Interpretability and explainability of generative models

Ethical and societal considerations: responsible use, audio deepfakes, cultural biases

Personalized support

Formation

PhD in relevant field

Description du poste

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

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

Job requirements

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

Additional information:

Localisation: Palaiseau (20km from Paris)
Type of contract: Permanent
Contact: Geoffroy PEETERS - [emailprotected]
Full job description here

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.

Job details

Title

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

2026-03-15 23:59 (Europe/Paris)
2026-03-15 23:59 (CET)

Télécom Paris is a member of IMT (Institut Mines-Télécom), the leading group of engineering and management schools in France.