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Field
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of biomarkers associated with cardiomyopathy and cytokine release syndrome which are transferred to the photonic sensors. Your tasks will include: Designing and optimizing immunoassays, such as ELISA
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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Iterative Algorithms: Optimization and Control.” About the Project The focus of the project is the analysis of iterative algorithms arising from time discretizations of nonlinear evolutions of various kinds
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division 8.5 Planning, performing, and evaluating in-situ/4D computed tomography experiments Developing software for the quantitative evaluation of various image data sets (algorithms for detecting volume
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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 1 month ago
Transformation Processes" and "Artificial Intelligence and Sensor Technology" – it combines its strengths in teaching and research across institutes and faculties. At its locations in Cottbus and Senftenberg
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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 1 month ago
: “Energy Transition and Decarbonisation”, “Health and Life Sciences”, “Global Change and Transformation Processes”, and “Artificial Intelligence and Sensor Technology”. At its campuses in Cottbus and
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sensor data, with applications in disease modeling and the development of material science-based innovations. These efforts aim to optimize system performance and uncover novel biological insights in close
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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combine electronic components, micro and nano sensors and actuators with interfaces for communication. Fraunhofer ENAS develops individual components, the technologies for their production as well as system
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm