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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, this will include the refinement of clinical research data models, development of ingest and QA/QC pipelines, and support for geospatial data visualization. The work will be performed in several cloud and/or
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phenotyping activities within the SmartWheat project. Plan, organize, and conduct field trials and summer field activities in collaboration with the project management team. Develop pipelines for processing and
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Departments and Centers: Law Postdoc Appointment Term: 1-2 Year Term Appointment Start Date: July-September 2026 Group or Departmental Website: https://law.stanford.edu/arthur-and-toni-rembe-rock-center
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running computational pipelines for transcriptomic and multi-omics data analysis and interpretation. Within the scope of the project, you will have the freedom to propose and drive the direction
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Final radiology embedding package with trained models, reference segments, and documentation. Deliverable: D3.3 Cross-modality calibration and confidence scoring pipeline with interface specification and
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sustainability of novel treatment pipelines. Key domains include (i) microbial products for nutrition and health, mostly based on purple bacteria, alongside (ii) treatment solutions for nutrients and carbon from
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computational pipelines using R/Python Collaborate with clinical teams Prepare manuscripts and contribute to grant applications Mentor students and research staff Other duties as assigned Minimum Education and/or
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synthesis, structured extraction of claims/evidence, reproducible AI-in-the-loop pipelines, or evaluation/verification of model-generated outputs) is preferred. Additional Information Applicants must complete
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inference pipelines for soft biomechanical systems, including differentiable physics engines, to support interpretable analysis, parameter estimation, sensitivity studies and uncertainty quantification. By
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features. Build and test pipelines for pose detection, object tracking, optical-flow analysis, and gaze–scene alignment, in collaboration with computer vision researchers. Analyze large multimodal datasets