32 software-defined-network-postdoc PhD positions at Eindhoven University of Technology (TU/e) in Netherlands
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communication networks? Optical wireless links using highly directional steerable laser beams can securely serve a high density of devices at high data rates. Your project optimizes energy efficiency and develops
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energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter specializes
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on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you fascinated by the large role software plays in the control of high-tech systems? Are you
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network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you: Full-time employment for four years, with an intermediate assessment
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battery for thermal storage. The idea is to combine waxes obtained through pyrolysis of plastic waste streams, with ultra-conductive graphene networks, i.e., nanometer sized carbon platelets that transport
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. The second sub-project, a postdoc track, focusses on pedagogies or structures for guiding students in selecting competencies to be achieved as learning outcomes, through learning activities and assessment
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including faculty members, postdocs and PhDs working on diverse topics in the field of dynamical systems and control and its applications. This PhD position is jointly supervised by Nathan van de Wouw, Tom
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, and software engineering skills with prior experience implementing machine learning algorithms using well-known frameworks (e.g., PyTorch). Ability to work in an interdisciplinary team and interested in
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fully funded PhD position within the LowDataML doctoral network, focusing on developing innovative machine-learning approaches for drug discovery under low-data conditions. LowDataML aims to bridge