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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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of Zurich and Wageningen University & Research. The four-year STEPS project focusses on developing data-driven and machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite
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machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite missions (e.g., CO2M, TANGO, Sentinel-4/5). Your research will contribute directly to monitoring global efforts
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine learning with the physics of laser–matter
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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine