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models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in machine learning, computer vision, and medical
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receive guidance from a mentor and will learn about conducting research analysis within OP. You will engage with current OP staff on policy analysis projects and assignments in one of the following focus
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accordance with MCW/FMLH/CSG policies and procedures. The APP fellow will have a strong foundation in evidence-based practice and ensure an environment of safe, quality care. Learn More: General APP Fellowship
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and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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the High Performance Computing and Data Center, to be completed on campus by August 2026. This position collaborates with others in the growing machine learning and exoplanet subgroups within the Physics and
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postdoctoral fellow, committed to advancing inclusive and interdisciplinary science, to join an international team applying state-of-the-art machine learning technologies to stem cell and immune engineering in
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marrow transplantation and CAR T cell therapies, spanning basic science to clinical trials. For more information about Dr. van den Brink’s research, please visithere. Lab's Philosophy : We foster a
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the system Development of inverse design frameworks using machine learning Development of full simulation for the chip-scale chirped-pulse amplification Use the full simulation to guide system fabrication
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. Preferred Qualifications: Prior experience working with mouse models of cancer is strongly preferred; candidates without prior experience will be considered if willing to learn. Interest in tumor metabolism