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is seeking a highly motivated PhD candidate to work on a fundamental research project on systems and control theory for learning in neuromorphic circuits. Neuromorphic computing is an analog, brain
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Requirements Master Degree in Electrical Engineering Experience in design and implementation of analog integrated circuits Experience in using Cadence, Spectre, ADS/Momentum, Matlab Highly motivated student
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only of storing information, but also of manipulating, organising, and retrieving it through molecular data structures analogous to those used in computer science. Building on our pioneering experimental
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enable highly integrated electronic systems for quantum computing and sensing applications and offer unique opportunities for innovation in analog and mixed-signal circuit design. Your research will focus
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this project, you will determine the properties of an icy moon analog surface through a series of laboratory experiments accounting for gravity, temperature fluctuations, and radiation effects. Icy grains will
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computing and sensing applications and offer unique opportunities for innovation in analog and mixed-signal circuit design. Your research will focus on the development of integrated cryogenic temperature
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companies. The project has partners from eight different EU countries. All 15 Ph.D. projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications in
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only of storing information, but also of manipulating, organising, and retrieving it through molecular data structures analogous to those used in computer science. Building on our pioneering experimental
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DD sequences into HR-type schemes, and verifying coherence via fringe contrast and Allan deviation. This other objective is to assess robustness against realistic technical noise. To serve that purpose
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. Integrate mapped data into Brain Maps 4.0 and Chemopleth 1.0 (and analogous mesoscale standards), establishing and maintaining interoperability with EBRAINS and the BrainGlobe ecosystem. Collaborate with