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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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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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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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National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more
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Professional qualifications (required) Relevant PhD degree (e.g. computer science, machine learning, statistics) Experience in developing deep learning models for 3D point cloud data Strong programming skills
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leading Swedish industry partners in 6G and cloud computing, gaining unique opportunities to bridge academic research with real-world applications. Research environment The Optical Networks (ON) Unit
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PhD or MSc in a relevant field of research (Bioinformatics or Computational Biology). Extensive experience in R or Python software development. Understanding of types and properties of mass spectrometry
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program is designed for candidates who have completed their PhD within the last two years and have experience as