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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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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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the analysis of organizing processes and their outcomes. Methodologically, we value qualitative research methods highly and often adopt case study, field work methodology or social network analysis. The teaching
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is a lively and research-oriented group of scientists and support staff with a broad interest in information processing in humans and computers, and a particular focus on the signals they exchange, and
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behavioral neuroscience or signal processing (especially of bioacoustics data) Programming experience (e.g. Python, R, Matlab, etc.) Strong communication and collaborative skills and proficiency in spoken and
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Job Description DTU Electro invites applications for a PhD position in digital signal processing and machine-learning-enabled continuous-variable quantum key distribution (CV-QKD). The position is
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Design invites applications for a PhD stipend in the field of causal discovery and spatiotemporal analysis of brain signals. The stipend is within the general study programme Electrical and Electronic
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of causal discovery and spatiotemporal analysis of brain signals
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cellular and molecular mechanisms driving inter-individual variability remain poorly understood. This PhD project will focus on experimental validation of cellular states and signaling pathways identified by