Postdoctoral Researcher in Data Science Wood Technology

Materials science and technology are our passion. With our cutting‑edge research Empas around 1100 employees make essential contributions to the well‑being of society for a future worth living. Empa is a research institution of the ETH Domain.

The Empa Laboratory for Cellulose & Wood Materials (Wood Tec group) explores sustainable wood processing and innovative applications of wood materials to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods with a focus on computer vision to enhance wood utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project ().

• Develop machine learning models and computer vision algorithms for wood property analysis sorting and grading.
• Contribute to the TIMBERHAUS project by applying advanced image processing and AI methods for timber quality assessment.
• Integrate experimental data with computational models and collaborate closely with lab teams.
• Publish research findings, present at conferences and support PhD students.
• Help shape new research proposals and assist in securing funding.

• PhD in Computer Science, Data Science, Machine Learning or a related discipline.
• Proven experience in computer vision (e.g. image processing, deep learning, object detection, segmentation) and machine learning techniques.
• Programming skills in Python and relevant ML frameworks (Tensor Flow, PyTorch), experience with version control systems (e.g. Git).
• Strong publication record in reputable journals and conferences.
• Interest in wood technology or biomaterials is a plus.
• Excellent communication skills in English; proficiency in German is beneficial.

We offer a fully funded 1 year position with the possibility of extension in an inspiring multidisciplinary and international research environment at a leading Swiss institute. The successful candidate will have access to state‑of‑the‑art infrastructure and opportunities for collaboration within the ETH Domain. Professional development networking and participation in innovative projects are supported. We provide competitive salary and employment conditions in the Zurich region.

We look forward to receiving your complete online application including a letter of motivation, CV, certificates, diplomas and contact details of two reference persons. Please submit these exclusively via our job portal. Applications by e‑mail and by post will not be considered.

Intelligence Community Experience, Python, Spss, Microsoft Word, R, Regression Analysis, Windows, Stata, Microsoft Power point, Research Experience, Data Modeling, Writing Skills

Patricia Nitzsche Stv. Leiterin Human Resources / Dep. Head Human Resources

Employment Type:

Full‑Time

Experience:

years

Vacancy: 1