About the opportunity
A 2-year full-time postdoctoral position is available at the Visual Computing (VisCom) section of DTU Compute. The role is part of the HAV-INNO project, a multi-disciplinary collaboration focused on transforming underwater imagery into a quantitative tool for measuring species abundance. The successful candidate will develop AI-based methods for detecting and identifying fish in underwater video sequences, ensuring robustness across diverse environmental conditions. The position offers access to state-of-the-art facilities, high-performance computing resources, and opportunities to build a teaching portfolio and supervise students. DTU is a leading technical university known for its international, inclusive, and research-driven environment.
Salary and benefits
- Full-time employment for a 2-year period.
- Salary based on the collective agreement with the Danish Confederation of Professional Associations.
- Negotiable salary supplements in accordance with DTU’s salary structure for scientific staff.
- Access to state-of-the-art facilities and high-performance computing resources.
- Opportunities to build a teaching portfolio and supervise students.
- Professional networking through collaborations with industry and research institutions.
Who can apply?
- Must hold a PhD degree (or equivalent).
- Research background in deep learning and computer vision.
- Experience in developing methods for marine underwater images or similar.
- Experience handling high volumes of data.
- Self-motivated and highly independent.
Required documents
- Application (cover letter)
- CV
- Academic Diplomas (MSc/PhD – in English)
- List of publications
- Research statement, including how your background fits the position
When to apply
- Application deadline: 21 September 2026 (23:59 Danish time).
How to apply
- Open the 'Apply now' link on the official job page.
- Fill out the online application form.
- Submit all required materials as one single PDF file in English.
Additional information
- Starting date is December 2026 or according to mutual agreement.
- Open-source background checks may be conducted on qualified candidates due to research in critical technology.
- All interested candidates are encouraged to apply regardless of age, gender, disability, race, religion, or ethnic background.
- Further information can be obtained from Juan Miguel Valverde (jmvma@dtu.dk).
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…
- PhD holder with a research background in deep learning and computer vision
- Experience handling high volumes of data and developing methods for marine or underwater imagery
- Self-motivated researcher interested in interdisciplinary environmental projects
What should you think carefully about?
- The role is strictly on-site, which may require relocation to Kgs. Lyngby
- Candidates should be prepared for open-source background checks
- The position includes teaching and student supervision duties in addition to research
How could this fit your current goals and plans?
This two-year postdoc is an excellent opportunity for a computer vision specialist to apply AI to marine conservation and species abundance estimation. It allows the researcher to leverage high-performance computing resources and build a teaching portfolio in an inclusive, research-driven environment.
Our take
Computer vision researchers with a passion for environmental applications and a desire to build a teaching record should consider this role. It is less suitable for those who prefer purely theoretical work or remote research settings.
Ready to apply?
Review the opportunity on the official website before applying.
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