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Field
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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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workflows between field acquisition teams, data center staff, and research collaborators to ensure seamless data transfer and integration. -Support daily operations of servers, networks, storage, and cloud
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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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HPC, bwHPC cloud, secure pipelines). Design cross-site preprocessing and harmonization pipelines for multi-omics and functional drug screening data. Collaborate closely with European partners
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intelligence, software engineering, data management, distributed systems, or cloud computing Excellent communication and teamwork skills Strong organizational abilities with the capacity to work independently
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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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). Applicants with a background in either QIS or QFT are welcome. Our group has access to cloud-based quantum computing resources through IBM and AWS, and an IBM quantum computer is expected to be acquired soon
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locally, in the cloud and in the Galaxy workflow system. The successful candidate will focus on implementing improved data representation and storage modes for large-scale mass spectrometry (MS) data
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in St. Cloud offers a wide range of patient experiences throughout students’ education in Greater Minnesota and prepares them to become exceptional clinicians and leaders for rural and immigrant
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud