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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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networking, enable internationalization and mobility, and create a collaborative environment. TUM and the CRC embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving
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). The institute also maintains locations in Dedelow and Paulinenaue. The research group “Farm Economics and Ecosystem Services” is a team of dedicated postdocs and PhD students who want to make a difference through
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software. The TELOS collaboration, co-led by researchers at Swansea University and The University of Edinburgh, and with links in other Institutions in the United Kingdom, Taiwan, Korea, Austria and Japan
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rotating subfields of the Cluster and annual retreats of the doctoral researchers as well as welcome and networking events are part of the programme. HEiKA's offer contributes to the continuous deepening
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). The institute also maintains locations in Dedelow and Paulinenaue.The research group “Farm Economics and Ecosystem Services” is a team of dedicated postdocs and PhD students who want to make a difference through
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course is recommended, in order to enable students to fully participate in and profit from the network. Full-time / part-time full-time Programme duration 9 semesters or more Beginning Other Tuition fees
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and develop advanced cryogenic power electronics solutions for key net-zero applications such as all-electric aviation and wind energy. This fully-funded PhD project will provide the opportunity
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a strong career-defining network. The IntelliWind Doctoral Network provides training for a new creative, entrepreneurial, innovative, and resilient industry-oriented academic generation ready to face