Aalto University
1 week ago
Doctoral Researcher in Speech and Language Technology (AI-generated audio watermarking and deepfake detection) Aalto University in Finland
Degree Level
PhD
Field of study
Computer Science
Funding
Funded doctoral research position in the COWAMA project. Starting salary is 3143 €/month and increases after a mid-term evaluation. The position follows Aalto’s standard 2+2 model, initially for two years with a six-month probationary period and extendable by two further years after a successful mid-term review, for a total of four years.
Deadline
Oct 31, 2026
Country
Finland
University
Aalto University
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About this position
Aalto University is recruiting a Doctoral Researcher in Speech and Language Technology at the Department of Information and Communications Engineering (DICE), Finland. The project, COWAMA: Content-based watermarking for AI-generated audio, is led by Assistant Professor Lauri Juvela and focuses on speech and audio processing, deepfake detection, audio watermarking, source tracing, and trustworthy generative AI.
The research aims to detect the origin and authenticity of AI-generated speech and music, improve content-based watermarking, and test robustness against removal, spoofing, adversarial attacks, signal-processing attacks, and realistic downstream processing. The doctoral researcher will develop detection methods for generated audio from multiple models, build datasets of real and synthetic speech/audio, adapt detector baselines, and work on explainable and localized attribution methods.
The position offers access to Aalto’s high-performance computing resources, CSC national infrastructure including LUMI, and the Aalto Acoustics Lab. The work is embedded in an international collaboration network with Prof. Junichi Yamagishi (National Institute of Informatics, Japan), Prof. Xavier Serra (Universitat Pompeu Fabra, Spain), and Prof. Gustav Eje Henter (KTH Royal Institute of Technology, Sweden).
Applicants should have a master’s degree or be close to completing one in a relevant field such as speech/audio processing, machine learning, signal processing, computer science, or electrical engineering. Required strengths include Python/programming skills, basic deep learning knowledge, interest in speech/audio datasets and generative audio models, motivation for scientific publishing and open-source research, and good English. Finnish is not required.
The position is funded, fixed-term, and follows Aalto’s 2+2 doctoral model. The starting salary is 3143 €/month, with extension after a successful mid-term review. The work is primarily located at Otaniemi Campus, Espoo, Finland. Deadline: 31 October 2026.
Funding details
Funded doctoral research position in the COWAMA project. Starting salary is 3143 €/month and increases after a mid-term evaluation. The position follows Aalto’s standard 2+2 model, initially for two years with a six-month probationary period and extendable by two further years after a successful mid-term review, for a total of four years.
What's required
A master’s degree, or near completion of a master’s degree, in speech or audio processing, machine learning, signal processing, computer science, electrical engineering, or a related field is required. Applicants should have strong interest in doctoral research on audio deepfake detection, watermarking, source tracing, and generative AI; good programming skills, preferably 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 independently and collaboratively in an international environment; and fluency in English. Finnish is not required.
How to apply
Apply through Aalto University’s recruitment site via the “Apply now!” button. Submit your CV, motivation letter, and copies of degree certificates and academic transcripts by 31 October 2026 at 23:59 EET. For role questions, contact Lauri Juvela; for application process questions, contact HR Advisor Johanna Haapalainen.
More information can be found here
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