33 post-doc-in-wireless-communication-and-networks-2016 Postdoctoral positions at Chalmers University of Technology in Sweden
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-capacity wireless communication solutions. As part of a cross-disciplinary team, you will be expected to present your research results at project meetings, co-supervise PhD students, and contribute
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(CS) group at the division of Communications, Antennas, and Optical Networks (CAOS) , Department of Electrical Engineering . The group consists of nine professors and a large number of PhD students and
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research and education with a focus on wireless electronics, photonics, quantum technology, as well as bioelectronics and microelectronics packaging and integration within Chalmers University of Technology
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To fully benefit from automated vehicles (AVs), they must be both safe and appreciated by drivers. This post-doc is to use modeling (e.g., AI/machine learning) and behavior data to predict perceived
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of managing reverse logistics for returned products, and the potential disruptions to existing distribution networks. About us and the research project The division of Supply & Operations Management (SOM
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engineering students within the area of bioengineering. It is furthermore collaborating in broad, interdisciplinary national and international networks within academia and the industry. The division of Food and
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are active members in the ALERT Geomaterials network and many international committees. Our international team with over 15 full-time researchers offers a great working environment to learn and develop. In
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, independent and with a well-developed analytical problem-solving ability. As a person, you are empathetic, loyal and have high ethical standards. Your communication skills in English (literal as well as oral
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As the successful candidate you will play an essential role in the development of blue or UV PCSELs. These devices have potential applications in lithography, disinfection, underwater communication
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understanding as well as manipulating its function can have a profound impact. Due to the complexity of metabolic networks, computational models serve as powerful tools. This project focuses on developing