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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do The complete design and implementation of analog circuits including
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 22 hours ago
Degree PhD Course location Kaiserslautern Teaching language English Languages Discussions are held in English (100%). Programme duration 8 semesters Beginning Only for doctoral programmes: any time
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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international research environment covering a wide variety of research areas, such as algorithms and data structures, machine learning, computer graphics and vision, database systems, artificial intelligence
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 22 hours ago
Degree Doctor of Philosophy (PhD) in Environmental Sciences Course location Cottbus Teaching language English Languages All courses are taught in English. The dissertation is written in English, and
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take place monthly. A lecture series on theoretical and experimental neuroscience as well as machine learning is addressed primarily to doctoral students. Lectures are held by principal investigators
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offers the possibility of a doctorate. What you bring to the table Bachelors, Masters, or a PhD degree in Electrical Engineering or equivalent technical field > 1 years of related experience or equivalent
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with emphasis on medium access layer protocols (MAC), machine learning and LTE/5G procedures Excellent analytical understanding and research skills Creative thinking and interest in new technologies Self
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years of experience working with IEEE WiFi standards Strong background in wireless communication with emphasis on medium PHY or MAC, machine learning and WiFi procedures Excellent analytical understanding
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further