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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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Application Deadline 24 Sep 2026 - 09:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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approach for OFR, building further on existing methods; (2) quantify the value of OFR in Luxembourg ; (3) quantify the impact of forest disturbances on the OFR supply and value; (4) estimate the supply and
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Language Models for Data-to-Text Problems” and involves the study of technical methods and approaches for adapting large language models to tasks mixing text and structured data, such as statistical report
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Application Deadline 29 Aug 2026 - 01:06 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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concerning this position, please contact Prof. Stefan Braum, email: Stefan.Braum@uni.lu
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest