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Mechanical Engineering, Applied Mathematics, Computational Modelling, Acoustics, Materials Science, or a related discipline. Demonstrated experience in multiphysics simulation, digital twin development
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sciences, physics, engineering, or a related field Have experience in brain imaging (e.g functional ultrasound (fUS), fMRI; optical imaging, electrophysiology) Are proficient in the analysis of large-scale
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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process can be directed to Prof. Chen-Ting Liao (Liao3[at]IU.edu) Basic Qualifications: • Ph.D. in Physics, Chemistry, Quantum Information Science, Optics, Electrical Engineering, or a related field at the
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to ICFA collections for scholars and the public. The Fellow will be fully integrated into the Library and Pre-Columbian Studies Program and will work closely with the staff of the Image Collection and
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 4 days ago
that are acceptable for program participation. This program, administered by ORAU through its contract with the U.S. Department of Energy to manage the Oak Ridge Institute for Science and Education, was established
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enterprise and are within the top 1% of universities worldwide. Apply to be part of a Horizon Europe Pathfinder science-to-technology breakthrough, targeting a paradigm shift in fabricating a novel optically
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of PhD submission. Strong expertise in advanced confocal and/or light sheet imaging. Strong expertise in quantitative image analysis approaches. Excellent molecular biology skills. Strong interest and
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activities. You must have a PhD or equivalent in Biology, Palaeontology or another relevant subject area and proven knowledge of mammalian anatomy and evolution. Experience in working with morphological image
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities