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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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. About You You will have, or be close to completion of a PhD/DPhil in Statistics, Machine Learning, Data Science, or a related quantitative discipline. You will demonstrate strong specialist knowledge in
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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of strains) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modelling
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hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
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relevant to the content of the ROSETTA project (https://rosetta-project.eu/ ). Applications featuring a PhD in a behavioral science–related field (e.g., marketing, consumer behavior, psychology
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer