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and regional scales. Proficiency in programming (e.g., Python, R) and experience with machine learning for geospatial data analysis. A strong track record of publishing research articles in high-impact
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, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems , security and computational materials science. Description of the position and
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education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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. - Proven expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs
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. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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. Experience with modeling software and climate data analysis. Strong quantitative skills, including knowledge of statistical and machine learning methods. Proven ability to conduct independent and collaborative
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. Experience with modeling software and climate data analysis. Strong quantitative skills, including knowledge of statistical and machine learning methods. Proven ability to conduct independent and collaborative