11 sensor-algorithm-"Fraunhofer-Gesellschaft" positions at Linköping University in Sweden
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. The research includes artificial intelligence and autonomous systems that operate in collaboration with humans and adapt to their environment using sensors, information, and knowledge, creating intelligent
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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functionality of soft materials in devices such as diodes, transistors, solar cells, sensors, and energy storage systems, thereby contributing to improved efficiency and sustainability. Collaboration with
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on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems
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monitoring. These applications rely on remote sensors to capture PCs and wirelessly transmit them to edge servers for downstream tasks, such as registration, i.e., aligning multiple PCs within the same 3D
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like computational complexity of algorithms. It’s also fairly common that we need to drill down into the code for some tool to figure out what’s wrong, so being able to read and understand code is
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to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. Read more: https://wasp-sweden.org/ . The vision of WASP is excellent research and competence in artificial
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor