项目介绍

2026年8月20日

Are you interested in developing event-driven, energy-efficient methods for processing real-world acoustic signals, grounded in the physics of sound and the computational principles of biological hearing?

As our new colleague, you will help pioneer novel applications of neuromorphic computation in acoustics. By combining spiking neural networks, event-driven sensing, and classical acoustic signal processing, you will contribute to the development of next-generation acoustic sensing systems.

You will push the boundaries of:

• Continuous-time and sparse representations, exploiting the temporal structure of acoustic fields through event-driven and spike-based encodings rather than uniformly sampled frames.
• Auditory front-ends, inspired by cochlear processing and spike-based wavelet decompositions.
• Hardware realization, deploying always-on, low-power acoustic sensing solutions on mixed-signal and neuromorphic hardware platforms.
• Acoustic perception and scene analysis, addressing challenges such as source localization, detection, and classification using microphone arrays under stringent power and latency constraints.

Acoustics, signal processing, and a curious mindset
You are fascinated by how sound carries information and how it can be processed efficiently, and you have a strong interest in the mathematical and physical foundations of acoustic signal processing. You will be responsible for developing brain-inspired computational methods that open new approaches to acoustic sensing and inference. 

We are looking for a profile with the motivation and drive needed for making a difference that matters. You bring an open mindset and like to create results via collaboration with people from different professional and cultural backgrounds. 

You are a talented, self-motivated, and team-oriented person who enjoys working on the theoretical and applied foundations of acoustic machine learning. 

Your CV comprises:

• Solid foundations in signal processing and applied mathematics.
• Some background in acoustics and/or acoustic signal processing (e. g. array processing, time-frequency analysis, source localization, room or underwater acoustics).
• Experience programming machine learning models (e. g. PyTorch/Jax) and familiarity with spiking-network frameworks (e. g. snnTorch or Norse) or neuromorphic hardware is an advantage.
• An active interest in interdisciplinary work at the intersection of acoustics, machine learning, and neuromorphic engineering.
• You must be fluent in English, both speaking and writing and possess excellent communication skills.

As part of the Danish Ph.D. program, you will follow a number of Ph.D. courses as well as take part in teaching and supervision of students. The PhD further includes interesting opportunities for an external research stay.

You must have 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.

Approval and Enrolment 
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU’s rules for the PhD education. 

Assessment
The assessment of the applicants will be made by Professor Peter Gerstoft (DTU Electro).

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms 
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

The position is a full-time position starting 1 November 2026, or according to mutual agreement.

The workplace is DTU Lyngby Campus.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Professor Peter Gerstoft (DTU Electro) pegers@dtu.dk 

You can read more about “the Department” at https://electro.dtu.dk/

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. 

Application procedure 
Your complete online application must be submitted no later than 14 September 2026 (23:59 Danish time). 

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link “Apply now”, fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae 
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale