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Field
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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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Details Title Postdoctoral Fellowship in Visualization and/or Machine Learning at Harvard University School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area
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Details Title Postdoctoral Fellow in Machine Learning and Design of Biological Systems School Faculty of Arts and Sciences Department/Area Science Division Position Description A postdoctoral
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a track record in computational modelling that explores the dynamics of AI systems and the development of autonomous AI agents, experience with machine learning, reinforcement learning, and generative
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Computer Science, Biomedical Engineering, Pathology Informatics, or a related field, with emphasis on computer vision and machine learning (summer and fall graduates are also welcome to apply) Proficiency in
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devices, and edge computing platforms. Deploy machine learning models to enhance process control and system responsiveness. Collaborate with industry partners to identify research challenges, co-develop
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 18 hours ago
Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills, Training/Education
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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written and verbal communication skills regarding research results. Preferred Qualifications: Experience with deep/graph neural networks and active involvement in data science and machine learning projects
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both the NCRC in Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills