1,488 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at Nature Careers
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, it is critical that pediatric hematology/oncology practitioners understand and learn how to incorporate recent exciting yet complex discoveries surrounding germline genomics into the daily management
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Learning, AI-driven Scientific Discovery & Lab Automation, ML-driven molecular simulations, and beyond. We will support our Starting Principal Investigators with access to appropriate compute infrastructure
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testing. Experience of working with genomic data at a population scale, including the tools and technologies to manage sophisticated analyses. Experience of statistical and/or machine learning methods
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the home laboratory. Proven performance in earlier role/comparable role. Compensation In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of
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Scientist- Talbot Laboratory, Departments of Surgery and Bone Marrow Transplantation and Cell Therap
exceptional Scientist to lead studies in pediatric immune-oncology and solid tumor CAR T cell development. Our laboratory is part of a larger team of collaborative scientists within the Departments of Surgery
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within the project AI4TECSWriting a doctoral dissertation in computer sciencePublishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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human health. Within this mission, the Iorio Group works at the intersection of computational biology, functional genomics, and precision oncology, integrating machine learning, large-scale CRISPR
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with documentation and tracking systems/processes. Proven performance in earlier role. Compensation In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a
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the job. Compensation In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate
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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications