Postdoc position in the field of machine learning for wood grading in Zürich

We are seeking for an outstanding candidate with a strong background in the development and application of machine learning algorithms e.g. deep artificial neural networks to take up a challenging PostDoc position in the area of wood technology. Within the project, we intend to improve current wood grading processes for the construction sector by applying data-driven methods. The candidate will develop and adapt machine learning algorithms, e.g. deep neural networks with the objective of a more accurate prediction of relevant mechanical wood properties. Ultimately, this should result in a significantly improved grading of wood with high impact on the wood construction sector.

To tackle these challenging objectives, we are seeking for a highly motivated, creative and communicative personality that can bridge expertise between data science and wood technology. Required qualifications include a PhD degree in computer science, data science or related field with a strong background in machine learning, particularly in deep artificial neural networks. A basic understanding of wood and wood technology is advantageous, but not a requirement. We expect a track record of high-quality scientific publications. Very good communication and writing skills in English are required, good German language skills are beneficial.

 

You will be working in an international, science oriented team addressing diverse fields of wood science and technology at a research institution in the Zürich area with outstanding infrastructure and within a broadly interdisciplinary setting. The duration of this position is two years. The project will start January 1st 2019.