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Field
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over the course of the project. References: - Deneu B et al (2021) Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Comput
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grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations
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fabrication of bioelectrical platforms with clinical translation as the ultimate goal. Using unique bioelectrical (physical and chemical) sensors and actuators will allow us to tackle grand biomedical
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completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation
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offer an inspiring research setting at one of Europe’s leading technical universities, with access to unique test facilities and strong international collaboration networks. This position provides
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international collaboration networks. This position provides the opportunity to contribute directly to the energy transition and to the development of sustainable, scalable heating solutions for the built
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fabrication of bioelectrical platforms with clinical translation as the ultimate goal. Using unique bioelectrical (physical and chemical) sensors and actuators will allow us to tackle grand biomedical
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maintenance test facility at SDU. This includes dynamical simulation of breeding blanket extraction with a robot, design and implementation of real-time control system, selection of sensors and actuators
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system, and (2) a validated prototype of a multi-channel detection system for fish entering the net. The focus will be on implementing fish detection by combining measurements of time- and position
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. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming