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of optical oxygen sensors, establishment of protocols for sensor calibration, mechanical tests of in situ experimental platforms, data management, organization of shipping and logistics for fieldwork
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assistant professor level with proven experience in the development and testing of innovative methods and sensors to identify and potentially improve the quantification of the underlying physico-chemical and
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
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Postdoctoral Researcher Position in Digitalization of Metal Additive Manufacturing and CO2 Impact...
highly motivatedpostdoctoral researcher to contribute to this vision by leveraging digital twins, sensor integration, and data-driven sustainability assessments. The successful candidate will play a key
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The Department of Agroecology at Aarhus university has recently acquired state-of-the-art plant phenotyping infrastructure, including a diverse range of UAV sensors for canopy determination, a multispectral camera
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Senior Researcher in Design and Operation of Sustainable Biomanufacturing Processes - DTU Chemica...
knowledge of soft sensors, AI and ML, and hybrid modelling approaches, expanding also towards the digitalization of education, including the development of chatbots, virtual labs, and the customization
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new