Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 16 000 students and 5 200 employees, including 446 professors. Our campus is in Espoo, Greater Helsinki, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community.
The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI, and the Aalto Acoustics Lab with anechoic chambers, listening rooms, and audio measurement equipment.
We are now looking for a Doctoral Researcher in Speech and Language Technology
Are you excited about speech and audio AI, deepfake detection, and the question of how we can identify the origin of AI-generated content? We are looking for a Doctoral Researcher to join the funded project COWAMA: Content-based watermarking for AI-generated audio, led by Assistant Professor Lauri Juvela.
The rapid development of generative AI has made it possible to create realistic speech and music, but it has also created risks related to misinformation, malicious deepfakes, copyright, ownership, attribution, and accountability. The project addresses these challenges by developing methods for detecting the origin and authenticity of generated and watermarked audio data, improving content-based audio watermarking, and evaluating robustness against removal, spoofing, adversarial attacks, and realistic downstream processing.
Your role and goals
As the Doctoral Researcher, you will take primary responsibility fordetecting generated audio content from multiple sources, and work jointly with the Postdoctoral Researcher on robustness, evaluation, and generalization.
Your work will include:
Developing methods for detecting the authenticity and origin of speech and audio content generated by multiple models and containing different watermarking methods.
Creating datasets of diverse real and generated speech and audio, including content from different generative models and multiple watermarking methods.
Adapting and improving detector baselines for multi-objective detection involving deepfake detection, content origin detection, and watermark identification.
Developing explainable and localized detection methods for watermark and deepfake attribution, especially when generated content is mixed with other audio sources.
Studying robustness against signal-processing attacks, generative resynthesis attacks, adversarial attacks, and realistic downstream processing such as mixing.
Publishing research in leading journals and conferences in speech, audio, and machine learning, and contributing to open-source releases of software, trained models, and reproducible research outputs.
The research methods will include experiment design, software implementation, running deep learning experiments on high-performance computing infrastructure, and evaluation using objective metrics and subjective listening tests.
Your network and team
You will be supervised by Assistant Professor Lauri Juvela, who leads the Speech Synthesis research group at Aalto University. The group works on deep generative models for speech and audio, speech synthesis, differentiable signal processing, deepfake detection, and watermarking.
In addition to the Aalto speech groups and the Postdoctoral Researcher in the project, you will work with an international collaboration network including Prof. Junichi Yamagishi at the National Institute of Informatics in Japan, Prof. Xavier Serra at Universitat Pompeu Fabra in Spain, Prof. Gustav Eje Henter at KTH Royal Institute of Technology in Sweden.
The collaboration network has a strong background in speech and audio synthesis, deep generative models, and deepfake detection, positioning the project to make an impact in watermarking and source tracing for AI-generated audio.
Your experience and ambitions
We are looking for a curious and motivated early-career researcher who wants to develop expertise in speech, audio, machine learning, and trustworthy generative AI. To succeed in this role, you should have:
A master’s degree, or be close to completing a master’s degree, in speech or audio processing, machine learning, signal processing, computer science, electrical engineering, or a related field.
Strong interest in doctoral research on audio deepfake detection, watermarking, source tracing, and generative AI.
Good programming skills, preferably including Python and modern machine learning tools.
Basic knowledge of deep learning, signal processing, speech/audio processing, or statistical machine learning.
Interest in working with speech and audio datasets, detector models, generative audio models, and experimental evaluation.
Motivation to publish scientific articles and contribute to open-source and reproducible research. [
Ability to work both independently and collaboratively in an international research environment.
Fluency in English is required. Finnish language is not required.
If you are chosen for this position, you will apply for the study right in doctoral studies at Aalto University School of Electrical Engineering. Thus, please see the student information and admission criteria at https://www.aalto.fi/en/study-options/aalto-doctoral-programme-in-electrical-engineering.
What we offer
A doctoral research position in a timely and socially meaningful field: improving transparency, traceability, and accountability for AI-generated speech and audio.
The opportunity to work on technical methods that support safer use of generative AI, including deepfake detection, watermark attribution, and robustness evaluation.
Excellent computing and audio research infrastructure, including CPU/GPU clusters, access to CSC and LUMI, FIN-CLARIN resources, and the Aalto Acoustics Lab.
A supportive research team and supervision by Assistant Professor Lauri Juvela.
International collaboration opportunities with leading researchers in speech synthesis, music technology, deepfake detection, and generative audio.
A strong open-science environment: the project aims to publish in leading venues and release software source code and trained models to support reproducibility and FAIR data management.
Great possibilities for competence development and learning, including professional development opportunities, staff training, and development projects based on your interests and needs.
A culture guided by responsibility, courage, and collaboration, where equality and inclusion support curiosity, innovation, collaboration, and wellbeing.
Our vast array of professional development opportunities means you will grow and learn, having the chance to participate actively in staff training and development projects based on your interests and needs. The starting salary for this position is 3143 €/month and increases after a mid-term evaluation. The position is fixed term and follows school’s standard 2+2 model. It will be made initially for two years, with a six-month probationary period, and extended by two further years after a successful mid-term review, giving a total duration of four years. The position starts in January 2027 or as mutually agreed.
We value work-life balance and well-being in all aspects of life. We work in a hybrid model, with the primary workplace located at the Otaniemi Campus in Espoo, Finland. Life on the revitalized campus is vibrant, featuring stunning architecture, tranquil nature, and a variety of cafes, restaurants, and services, all complemented by excellent public transportation connections.
Join us!
To apply, please share your CV, motivation letter, and copies of degree certificates and academic transcripts with us through our recruitment site ("Apply now!” at the bottom of the page) at the latest on 31st October 2026 23.59pm (EET).
Please note: Aalto University employees should apply for the position via our internal HR system, Workday (Internal Jobs), using their existing Workday user account (not the external webpage for open positions). If you are a student or visitor at Aalto University, please apply with your personal email address (not aalto.fi) via Aalto University open positions
For more information about the role, please contact Professor Lauri Juvela ([email protected]; +358 50 464 6653). For questions about the application process, please contact HR Advisor Johanna Haapalainen at [email protected].
We will go through applications, and we may invite suitable candidates to interview already during the application period. You will hear from us the latest in the second week of November. We aim to have a transparent and equal recruitment process, so feel free to ask us for feedback.
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About Finland
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For more information about living in Finland: Aalto Careers for International Staff.
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