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biobanks in the country, enabling studies across diverse cardiovascular genotypes. A key component of this role includes applying advanced nanoparticle technology to track single GPCR molecules in
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
or related Engineering or Physics. Required Qualifications, Competencies, and Experience PhD degree in Biomedical/Electrical or related Engineering or Physics. Experience with MRI acquisition and data analysis
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biology techniques include molecular cloning, gene transfection and expression, siRNA technology, qPCR, FACS analysis, confocal imaging, histology, immunohistochemistry, immunofluorescence, ELISA, Western
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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of Engineering at the University of Texas at Arlington invites applications for a rank Post Doctoral Research Associate. This position will focus on analyzing imaging data, developing novel methods for analysis
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the benefit of humanity. GBI is part of the Ellison Institute of Technology, Oxford (EIT) and is led by founding Director Jason Chin. The vision of the Generative Biology Institute is to lay the foundations
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We are now looking to appoint a postdoc in organic bioelectronics, placed in the Laboratory of Organic Electronics at the Department of Science and Technology, Campus Norrköping. Research area To
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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework for tissue self