154 condition-monitoring-machine-learning-"Multiple" Postdoctoral positions in Denmark
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DTU Energy, we are working to enhance the mechanical robustness of cell and stack components and gain deeper insights into their behaviour under technologically relevant conditions. This includes
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assessment. Read about shortlisting at SDU. Interviews and tests may be part of the overall evaluation. Read about the Assessment and selection process . Conditions of employment Appointment as postdoc is
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
foundation in multiple cryo-EM structures. Here the postdoc will work closely together with a PhD student dedicated to this project. The single molecule data will be obtained by the postdoc at a local state of
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
comprehensive quantitative evidence and understanding of their capacity and cost-effectiveness for carbon sequestration under varying conditions. You will be part of a large international research project focused
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the disparities. While foundation models offer great promise for creating more robust machine learning models for a wide array of tasks, it remains an open problem how to foresee their biases across that wide array
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the foundations for reliable decision support and Monitoring, Reporting, and Verification (MRV) systems for reducing greenhouse gas emissions in Danish agriculture, particularly exploring conditions for the uptake
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hardware and fluidics. You are expected to: Design and build an automated fluidics system for deposition of chemical reagents with in-situ monitoring of film deposition using quartz crystal microbalance
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us to explore the relation between the degree and type of processing, and the foods that result from their use. The results will be used for data machine learning, in collaboration with other partners
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design