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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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, enabling energy-efficient, quiet, and long-duration monitoring of ecosystems. The research will integrate novel lightweight perception modalities for robust perching in the wild, agile control algorithms
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, cargo, harbors etc. Large and deep AI models can be built using these data sets and machine learning, which can be combined with real-time satellite-based AIS data and sensors such as radar and algorithms
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to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track mutations in evolving populations
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research center and two 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
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. For example, we would like to be able to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track
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skills and motivation to implement algorithms and test them in practice on large-scale problems. Programming Skills: You are proficient in at least one scientific programming language (such as Python
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
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communication Autonomous driving algorithms and technologies (e.g. vehicle control, path planning, scheduling) and sensors (e.g. lidars, radars, cameras, and GNSS) High-level integration of autonomous driving
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms