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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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electrochemical measurements (e.g. cyclic voltammetry) and electron paramagnetic resonance (EPR) spectroscopy data. Your profile In accordance with the European Union's funding rules for doctoral networks
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architecture, including a focus on applications, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Photonics is a promising platform as it provides
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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under multiple environmental and socio-economic scenarios. You’ll develop sought-after skills in geospatial analysis, hydrodynamics, sediment transport, machine learning-assisted detection, and hydro
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willingness to work in collaborative projects with multiple partners and present results at conferences, project meetings and partners; Very good English language skills (German is not required, but beneficial
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to apply. The University is a certified family-friendly university. We welcome applications from candidates with disabilities. If multiple candidates prove to be equally qualified, those with disabilities
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current and future disease risk and burden across multiple pathogens with environment- and climate-sensitivity. Your tasks: Building a diverse set of models for short-term predictions and the long-term
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operation, is not considered in the CMF model due to the challenge to solve the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and
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current and future disease risk and burden across multiple pathogens with environment- and climate-sensitivity. Your Tasks: Building a diverse set of models for short-term predictions and the long-term