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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, Competencies, and Experience Experience in cardiovascular modeling and simulation. Preferred Qualifications, Competencies, and Experience Experience with software development and/or high-performance computing
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, biomedical informatics, or a related field. Job Description: The Department of Health Outcomes and Biomedical Informatics (HOBI) seeking a Postdoctoral Associate with a background in human factors, industrial
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ideal for a researcher who possesses working fluency across both computational AI architectures and physical lab automation. We are seeking someone with an eagerness to master missing domains and a strong
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software that makes these methods usable and reproducible for other researchers. Design and execute computational studies that assess model performance, sensitivity, and parameter identifiability, and that
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direct biomedical relevance. We are embedded in both the VIB Center for AI & Computational Biology —a young, ambitious center whose research groups address biological questions through the lens of AI—and
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. Working at the interface between scientific computing, image analysis and research infrastructures, you will collaborate closely with scientists, software engineers, beamline scientists and computing
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present scientific results. # Software and tools - Proficiency in standard computer tools. - Experience with mass spectrometry data processing and analysis software. # Personal skills - Autonomy, rigor, and
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students. Designing novel experiments and concept in several basic, translational, and clinical projects in metabolic diseases and pregnancy disorders Good computer literacy including databases, standard
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Systems and Software Program (WASP ). You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one
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. Proficient with scientific computing and data-analysis software; experience with MATLAB, Python, R, or related platforms is strongly preferred. Experience with intracranial EEG (iEEG/ECoG/SEEG) or multichannel