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of small pixels and spectral requirements), interferometric techniques rely on comparing an interferogram imaged by the detector array with a simulated interferogram prior to detection. Through processing in
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varied terrains. TALC intends to advance the integrated system from Technology Readiness Level (TRL) 4 to TRL 6, demonstrating a prototype in a relevant operational environment. The project seeks
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, clinical language intelligence, and AI-driven healthcare implementation. https://www.uta.edu/academics/schools-colleges/engineering/research Responsibilities The ideal candidate will be an internationally
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will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
and teaching, the professorship will represent functional cardiovascular imaging with a focus on hemodynamic modeling and act as a bridge between basic research, medical technology development, and
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, including optical instrumentation, prototype device assembly, sensor characterisation, or microfluidics. Desirable: B1 A PhD in a relevant field (e.g. physics, engineering, applied photonics, or analytical
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Engineering, or related field. • Demonstrated expertise in deep learning and AI methodologies. Experience in medical image analysis, particularly applied to cancer research (pathology, MRI, CT scans) preferred
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, as well as in scientific computer tools for data and image analysis (ImageJ, Image Lab and GraphPad). Participation in scientific dissemination activities (conferences, seminars, Research Night, Area
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, functional, and molecular imaging data. This multimodal technology is optimized for preclinical research in oncology, neurobiology, embryology, and cardiology. Its non-invasive nature allows longitudinal