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of machine learning tools. Fellowship Details: The fellowship is for 3 years, with possibility of extension. Please submit a cover letter, including experience and motivation, and your full CV to rvr
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, computer science, bioengineering, data science, or a closely related discipline. • Demonstrate advanced proficiency in artificial intelligence and machine learning, particularly in applications involving
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field. Proven experience in multi-omics data integration, omics data analysis (genomics, transcriptomics, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and
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are leaders in such disciplines as genome-editing, AI/machine learning, protein engineering, cryo-EM/ET, NMR, single-molecule experiments and more. You will also collaborate with the wider community at St. Jude
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. As a Carnegie Doctoral/R2 institution, our world-class scholars instruct about 26,000 students in associate's, bachelor's, master's and doctoral level degree programs. Whether you are seeking the charm
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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Outstanding Postdoctoral Training Strategy
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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environment and governance will be highly desirable. Experience in computational social science, causal inference, text mining, machine learning, analysis of unstructured and multimodal data, or advanced
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 4 days ago
framework that maximizes sensitivity to the targeted model parameters. In addition, one could also study the separation of partial data, for instance using learning techniques. The applicant will review
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. [Work content and job description] (Immediately after hiring) Construction of a machine learning model describing the relationship between input data (such as solar cell structure, fabrication process