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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from November 2025, or as
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are not limited to, Developing new computational methods and analytical tools, with particular emphasis on machine learning and artificial intelligence approaches. Identifying signatures of viral adaptation
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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Electrical and Electronic Engineering, or related field. Research experience with Artificial Intelligence/Machine Learning/Large Language Model. Publication track record in a series of top tier conference
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collaborative mindset and excellent communication skills in English. Significant Advantage: Previous experience with adversarial machine learning, offensive security, or publications in top-tier conferences (e.g
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for wheat, barley, oat, and rye. As part of a highly collaborative, multi-disciplinary team, the selected candidate will use his/her computational biology and machine learning background to help develop tools
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about the most recent advances in machine learning and data management in agricultural research. The participant will have the opportunity to collaborate with multiple USDA ARS scientists on using machine