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. This includes: • Developing targeted campaigns that highlight faculty research, student success, and innovative programs—key metrics in ranking algorithms such as U.S. News & World Report, QS World University
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biomedical research projects using programming, data-mining, statistics, machine learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude
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debugging and profiling Parallel numerical algorithms and libraries System software stack administration and novel/experimental hardware. Over the course of the appointment, the candidate will be supported
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Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to contribute to our lab’s mission of aligning machine learning (ML) models with algorithmic reasoning tasks. Our goal is to
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insights from geometry and topology to discover new applications of machine learning. Multiple positions may be available. Role Requirements The successful candidate must have a PhD (or close to submitting
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issues or areas of critical data examination. Works with statistics on defining and documenting programming endpoint algorithms across a study, drug program and/or contributing to TA level algorithms
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. Given their importance, continuous monitoring and fault diagnostics are crucial—especially as machine learning algorithms play an increasingly prominent role in predictive maintenance and reliability
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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can reduce model accuracy, especially when modeling multiple processes that interact across different spatial scales. To address this, the project will develop a new class of raster data-processing