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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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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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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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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | about 2 months ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and
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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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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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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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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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these challenges by advancing machine learning (ML)-based and data-intensive methods for the scalable design, processing, and deployment of DPPs. The advertised PhD position focuses on developing ML-based and
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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