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, such as sedimentation, meltwater flow, and vegetation change, into active drivers of adaptive design. This interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and
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reviewed scientific publications. Your profile PhD in Computer Science, with specialization on applied machine learning, statistical methods, and/or software engineering Strong programming skills Strong
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classification, segmentation and regression using combinations of high-resolution LiDAR point cloud data and image data and may draw upon aspects of synthetic data-based learning and domain adaptation. To learn
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& Experience (specific to the project): PhD in Computer Science, Cybersecurity, Artificial Intelligence, or a related discipline. Strong research background in virtualisation, cybersecurity, AI or threat
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, Statistics, Epidemiology, or Computer Science -Highly qualified and motivated investigator (PhD, or MD/PhD) Preferred Qualifications: -Experience in statistical methods and analysis using SAS, R, or STATA. Pay
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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populations. Founded in 1888, the University of Minnesota Medical School has three campuses. A four-year MD program and the MD/PhD program are located on the Twin Cities campus in addition to MD programs
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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collaborations. We are looking for candidates with a PhD in remote sensing, geoinformatics, computer science, or a related field. Experience in handling multi-source EO data, 3D mapping, and geospatial analysis
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer