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English Proficiency in machine learning and large omics data analysis is preferred. Where to apply Website https://www.lih.lu/en/job/?value=JA/PDGMB0326/MD/DIIA Requirements Research FieldComputer science
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advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. He/she will support the development of an improved forest RTM that can
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and
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learning, computational biology, and AI for science The postdoc will work at the interface of machine learning, genomics, and scientific computing, contributing both methodological innovation and
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/admittance, force control Experience with Artificial Intelligence and deep learning concepts for robotics computer vision, tactile sensing, reinforcement learning Experience with robotic simulation tools e.g
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graphs and related structures, limit theorems, stochastic calculus and applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems
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training covering topics such as computational modelling, numerical methods, statistical analysis, machine learning or data-driven analysis of complex systems Experience 0–3 years of postdoctoral experience
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors