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Required qualifications: PhD in evolutionary ecology or related fields Strong track record of publishing scientific research Familiarity with urban evolutionary biology and wildlife biology. Strong ability
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the disparities. While foundation models offer great promise for creating more robust machine learning models for a wide array of tasks, it remains an open problem how to foresee their biases across that wide array
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that the candidate has prior research experience in one or more of the following research topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning
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-biology-neurobiology-and-anatomy/people/xuelin-lou-phd ). Postdocs are essential to the scholarly mission of the mentor and host institution, and thus are expected to have the freedom to publish the results
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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-dimensional probability, concentration and functional inequalities ? Mathematical aspects of machine learning and deep neural networks ? Free Probability aspects of Quantum Information Theory. While excellent
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design