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Sentinel-1/2 time series. Strong proficiency in Python for geospatial data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written
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design. Perform large-scale computational screening using first-principles calculations and machine-learning potentials. Analyze structure–property relationships and extract scientific insights from AI
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into real impact. At the division of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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Qualifications The following qualifications and experience will be considered an advantage: Experience with crop modeling. Experience with plant breeding. Background in data science, machine learning, and
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models for inverse materials design. Perform large-scale computational screening using first-principles calculations and machine-learning potentials. Analyze structure–property relationships and extract
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, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD
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of Data Science and AI , we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and
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within the Department of Electrical and Information Technology works broadly with research within Cryptography, Computer Security, Wireless and Fixed Networks. The security group has around 20 members
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on the candidate’s profile and selected research track. About the research project DRIVE PR – Data-Driven Product Realisation is a large collaborative research initiative at Chalmers University of Technology and the