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Samuel A. Verburg

4 months ago

PhD Position in Machine Learning for Acoustic Sensing under Uncertainty (Microphone Array Signal Processing) Technical University of Denmark in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

Denmark

University

Technical University of Denmark

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Keywords

Computer Science
Signal Processing
Electrical Engineering
Mathematics
Statistical Analysis
Numerical Analysis
Measurement Science
Transducer Technology
Optimisation
Acoustic Physics
Acoustic Sensing
Inverse Problem
Statistic
Physics
Noise And Vibration
Room Acoustic
Machine learning

About this position

This PhD position at the Acoustic Technology group, DTU Electro, offers an exciting opportunity to advance research in machine learning and statistical signal processing for microphone array data, with a particular focus on acoustic sensing under uncertainty. The successful candidate will join a creative and diverse scientific environment, collaborating with leading experts and contributing to the Alliance project 'Machine Learning for Acoustic Sensing under Uncertainty,' which is conducted in partnership with Aalto University and funded by an internal DTU grant.

The research group specializes in the generation and transmission of sound, acoustic signal processing, advanced measurement techniques, transducers, room acoustics, vibration, and numerical methods. As a PhD candidate, you will conduct original research in microphone array processing, develop novel algorithms to improve the robustness and accuracy of acoustic measurements, and address real-world challenges in acoustic sensing. You will have opportunities to present your work at international conferences, participate in training activities, contribute to teaching and mentoring MSc students, and engage in dissemination activities within the scientific community and to the public.

The position requires a two-year master's degree (120 ECTS points) or equivalent, with demonstrated experience in acoustic signal processing, microphone array processing, statistics, machine learning, optimization, and inverse problems. Excellent communication skills are essential. The appointment is for three years, based on the collective agreement with the Danish Confederation of Professional Associations, with the allowance agreed upon with the relevant union. DTU is a globally recognized technical university, offering a stimulating international environment and a commitment to academic excellence, collegial respect, and academic freedom.

The department employs over 300 researchers and is dedicated to sustainable energy, greener internet, cyber security, and health technology. DTU fosters an inclusive and evolving working environment, with campuses across Denmark and Greenland and collaborations with top universities worldwide. Applications must be submitted online by 13 November 2025, including all required materials in English as a single PDF file.

The assessment will be conducted by Assistant Professor Samuel A. Verburg (DTU), Assistant Professor Filip Elvander (Aalto), and Associate Professor Finn Agerkvist (DTU). For further information, candidates may contact Samuel A.

Verburg. DTU supports international applicants and offers resources for relocation and integration into Denmark.

Funding details

Available

What's required

Applicants must hold a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree, preferably in a relevant field such as acoustics, signal processing, electrical engineering, or related areas. Demonstrated experience in acoustic signal processing, microphone array processing, statistics, machine learning, optimization, and inverse problems is required. Excellent communication skills are expected. You may apply prior to obtaining your master's degree but cannot begin before having received it. All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

How to apply

Submit your complete online application by 13 November 2025 via the 'Apply now' link. Attach all required materials in English as a single PDF file, including a cover letter, CV, grade transcripts, and BSc/MSc diploma with grading scale. Applications received after the deadline will not be considered.

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