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Field
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, privacy, and resilience. Today’s Transformers models scale poorly and assume abundant cloud resources. The research program FIND aims to deliver architectural and algorithmic breakthroughs that enable
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in Physics, Mathematics, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. • Experience in data-reuploading quantum algorithms
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quantum algorithms, optical quantum computing and quantum machine learning (highly desirable). • Experience in machine-learning schemes based on arrays of nonlinearly interacting mechanical oscillators
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will be developed. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also
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, high school timetabling, examination timetabling, master thesis defense assignments and scheduling and student project and master’s thesis assignments. For these problems, we wish to develop an algorithm
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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-terminal antennas and beamforming operating in FR1 bands and future FR-2, enabling robust terrestrial–satellite integration for safety-critical air mobility services. To develop AI-based algorithms
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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Antenna Design: Developing innovative antenna systems compatible with metal detector coils, optimized for tasks such as minimum-metal landmine detection and deep object detection. Low Power, Compact