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results and conduct analytical modelling and numerical simulations (e.g., finite element modelling) to support experimental findings and predict performance. Independently implement and execute the research
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results and conduct analytical modelling and numerical simulations (e.g., finite element modelling) to support experimental findings and predict performance. Independently implement and execute the research
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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
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hydrogen detection: development of a field-deployable electrochemical method, benchmarked against lab-based approaches. Area 3 (Contact Person Dr Andreas Borgschulte ) Hydrogen permeation in model systems
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motivated Postdoctoral Researcher to join an applied research project focused on the development of AI/ML-based methods for the automation of laser processing techniques. In close collaboration with our
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integration of novel methods for replacing animal testing. The project involves collaborations with several leading European research groups and experts in the field. The Postdoctoral researcher will perform
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to support the development of sustainable, resilient, and
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of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid deposition and automated multi-technique characterization. Within the Swiss-Polish innovation
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development X-ray based methods focusing on the evaluation of the structure – property relationship in applications such as biomedicine and space. In the frame of an ESA project interfacing research and
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Thun explores the possibility of high throughput materials development. In the context of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid