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/or process simulation. Strong background in microscopy and imaging. Demonstrated ability to prepare scientific manuscripts and presentations. Ability to work independently and collaboratively across
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engineering-based research applicable to cardiovascular disease as part of an extramurally funded project. The successful applicant will create computational models from medical imaging data and run simulations
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders
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Postdoctoral Research Associate - Human Organoid/Assembloid Models of Schizophrenia-associated Risks
animal and human cellular models Single-cell profiling Advanced image processing and analysis Rodent behavior testing facilities In addition, numerous institutional shared resources and core facilities
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and scripting • Experience with medical image (MRI, DWI, CT) processing using open-source programs such as Seg3d, Slicer, ANTS, or similar • Experience DSI Studio, MRTrix, or similar • Experience with
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ways to reduce agricultural or food waste and introducing new food or material products in waste management systems. The ideal candidate will bring expertise in fermentation and non-chemical processing
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, Ecology, or a closely related field. Demonstrated expertise in processing and analyzing remote sensing data (hyperspectral and/or Lidar is a strong plus). Strong proficiency in programming, particularly in
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qualifications as specified by the Principal Investigator. PREFERRED QUALIFICATIONS: Familiarity with optical design, image processing, or instrument prototyping. Programming skills in MATLAB, Python, or LabVIEW
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Experience with imaging data processing, anatomical or functional registration, and 3D planning/reconstruction for recording trajectories Required Application Materials: CV One-page statement of interest
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cognitive, clinical, genetic, and proteomic data and manages them in the data repository and computer servers. Runs existing PET/MR brain image processing pipelines on the computer servers, produces