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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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prior to the application deadline Research experience with deep learning architectures (e.g. Transformers, diffusion models, graph neural networks) applied to multimodal data. Proven expertise in time
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the University of Beira Interior, Covilhã, Portugal, under the following conditions: Scientific Area: Electrical and Computer Engineering. Objectives: To develop an interoperable transducer network to support the
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global medical challenges. A postdoctoral position is available immediately for applicants interested in developing novel wearable optical sensors for applications in maternal health. The goals
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biologging multi-sensor acoustic tags on bats and toothed whales in the wild and combine these data with array recordings, noise playbacks and phantom target generators on trained animals in the lab
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and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
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data from measurement and observation networks, as well as snow testing protocols, to provide access to a larger, harmonized information system on both sides of the border; Mutual training and
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such as the electricity 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
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans. Analyzes complex sensor data, works with a multidisciplinary team to develop health digital
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sustainable development. With state-of-the-art infrastructure, UM6P has built a strong academic and research network and seeks to recruit high-quality professionals to enhance its research- focused environment