PhD scholarship in Automated Optical assessment of Marine Biofouling - DTU Chemical Engineering
On-site · Kongens Lyngby, Capital Region, Denmark or Hundested, Capital Region, Denmark
Job Summary
Develop, validate, and apply automated optical methods for quantitative biofouling assessment on coated test panels; build and improve robust image-analysis pipelines for large underwater image datasets; apply classical machine learning, neural networks, or segmentation models for fouling detection and quantification; contribute to the deployment and maintenance of underwater imaging systems; study biofouling processes such as growth, detachment, and regrowth under static and dynamic testing; collaborate across coating science, marine testing, imaging, and data science; supervise BSc and MSc student projects; disseminate findings through peer-reviewed publications and international conferences; complete PhD courses and TA work as part of the DTU PhD programme; contribute to the development of CoaST and DTU's research community.
Required Qualifications
- Two-year master’s degree (120 ECTS points) or equivalent
- Engineering discipline preferred (e.g., mechanical or chemical engineering)
- Strong programming skills (Python)
- Experience with image analysis, computer vision, scientific imaging, or signal processing
- Interest in machine learning and data-driven research
- Ability to work independently and collaboratively
- Good English communication skills
- Approval and enrolment in DTU PhD programme
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