About the opportunity
DTU Electro invites applications for a 3-year PhD scholarship focused on developing event-driven, energy-efficient methods for processing real-world acoustic signals, grounded in the physics of sound and biological hearing principles. The successful candidate will pioneer novel applications of neuromorphic computation in acoustics by combining spiking neural networks, event-driven sensing, and classical acoustic signal processing. Research areas include continuous-time and sparse representations, auditory front-ends, hardware realization on mixed-signal/neuromorphic platforms, and acoustic perception and scene analysis. As part of the Danish PhD program, the candidate will complete PhD courses, engage in teaching and student supervision, and have opportunities for an external research stay.
Salary and benefits
- Salary and appointment terms based on the collective agreement with the Danish Confederation of Professional Associations, with allowances agreed upon with the relevant union.
- Full-time employment for a period of 3 years.
- Opportunities for an external research stay.
- Participation in PhD courses, teaching, and student supervision as part of the Danish PhD program.
Who can apply?
- 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 (applicants may apply prior to obtaining their master's degree but cannot begin before receiving it).
- Solid foundations in signal processing and applied mathematics.
- Background in acoustics and/or acoustic signal processing (e.g., array processing, time-frequency analysis, source localization, room or underwater acoustics).
- Fluent in English, both speaking and writing, with excellent communication skills.
- 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.
Required documents
- A letter motivating the application (cover letter)
- Curriculum vitae (CV)
- Grade transcripts and BSc/MSc diploma in English, including official description of the grading scale
When to apply
- Complete online application must be submitted no later than 14 September 2026 (23:59 Danish time).
- Position starts 1 November 2026, or according to mutual agreement.
How to apply
- Open the online application link.
- Fill out the online application form.
- Prepare all materials in English and combine them into one single PDF file.
- Upload the PDF file and submit the application before the deadline.
Additional information
- The workplace is DTU Lyngby Campus.
- Assessment of applicants will be conducted by Professor Peter Gerstoft (DTU Electro).
- As DTU works with research in critical technology subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates.
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- Master’s degree holders with a solid background in signal processing, applied mathematics, or acoustics.
- Candidates with experience in machine learning frameworks like PyTorch or Jax, particularly those familiar with spiking neural networks.
- Individuals motivated by interdisciplinary research that combines biological hearing principles with neuromorphic computation.
What should you think carefully about?
- The role is on-site in Kgs. Lyngby, Denmark, and involves teaching and student supervision duties.
- The research involves critical technology, which may lead to open-source background checks.
- Applicants must be prepared to integrate into the Danish PhD program, which includes mandatory coursework.
How could this fit your current goals and plans?
This 3-year scholarship provides a structured environment to pioneer energy-efficient acoustic signal processing. It is perfect for a candidate aiming to bridge the gap between theoretical acoustics and hardware-level neuromorphic implementation.
Our take
Highly recommended for researchers with a strong mathematical and signal processing background. Candidates who prefer purely theoretical work without hardware or teaching components may find this less ideal.
Ready to apply?
Review the opportunity on the official website before applying.
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