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machines by interpreting brain activity (e.g., EEG signals) in real time using energy-efficient neuromorphic hardware. You will work on the design and hardware realization of Spiking Neural Networks (SNNs
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the new generation of Doctoral
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communities to cascading hazards, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the
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for brain signal acquisition Implementing an on-chip neuromorphic processor with a spike encoder and spiking neural network Developing a low-power spike-based transmitter. Setting up measurement systems and
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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by the POLIMA Center and its extensive network of international collaborators. POLIMA is a Center of Excellence funded by the Danish National Research Foundation (DNRF) for an initial period of 6 years
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the Spiking Neural Network (SNN) itself. However, close collaboration with another PhD student working on the SNN hardware design is expected to ensure seamless signal interfacing and system integration. Key
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.” This position is part of the IntelliWind (Intelligent Systems for Autonomous Wind Power Plant Operations) project, a prestigious Marie Skłodowska-Curie Doctoral Network (MSCA DN) funded by the European Union. As