64 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Luxembourg
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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order to better understand, explain and advance society and environment we live in. Your role The PhD position is embedded within the MICRO-PATH Doctoral Training Programme, funded by the Luxembourg
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The PhD position is embedded within the MICRO-PATH Doctoral Training Programme, funded by the Luxembourg National Research Fund. MICRO-PATH, or Pathogenesis in the Age of the Microbiome (https
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and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with more than 50
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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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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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Environmental behaviour o Spatial analysis applied to territorial/regional planning Technical and soft skills · Basic computer skills (Word, Excel etc.) · Proficiency in statistical analysis
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Application Deadline 29 Aug 2026 - 08:26 (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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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
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote