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leader • Excellent written and oral communication skills Preferred Qualifications • Background in antisemitism studies • Experience with R, NLP and deep learning libraries • High performance computing
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healthcare system, comprising the largest physician network in Indiana, 16 hospitals across Indiana, and a deep academic partnership with the IU School of Medicine. Ideal Candidate Profile: An established NIH
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch, TensorFlow). Experience working with multimodal
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from candidates with professional expertise in the area of finance and development. Successful candidates should be able to teach in the areas of development implementation and the finance of development
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are expected to teach at the undergraduate and graduate levels, and collaborate across disciplines to address real-world data challenges. Example areas include, but are not limited to: Machine learning and deep
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Core job duties include: (1) Designing, implementing, and
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an online environment and five or more years of professional (industry) experience in one or more areas of expertise listed above. A deep understanding of career opportunities in the information professions
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Indianapolis: IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments