577 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Nature Careers
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of security related experience (e.g., security program, police organization, military branch, conflict counselling). Experience in data entry and working in emergency situations and fast pace stressful
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Two Postdoctoral Researchers in Cell Delivery-Based Beta Cell Replacement Therapy for Type 1 Diabete
applications, often taking on an interdisciplinary character. Cutting-edge contributions to areas such as computer systems, theoretical computer science, cybersecurity, computer vision, artificial intelligence
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of this project is to translate this discovery into a clinically relevant assay. The role involves developing and optimizing the assay to maximize sensitivity and specificity using deep learning, spatial biology
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is a plus Strong organizational, communication, and time-management skills A proactive, problem-solving mindset and eagerness to learn Ideal commitment to at least 2 years of full-time research before
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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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, including CAR-T cell therapies. Qualifications: Applicants must hold an MD, PhD, or MD-PhD. A strong background in immunology, neuroscience, and/or cancer biology is essential. Prior experience with iPSCs
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to teach an undergraduate course focusing on essential principles of effective teamwork, leadership, communication, and conflict resolution, with a special emphasis on the role of Human-Centered AI in
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to teach an undergraduate course, "From Vision to Execution," focused on core project management principles for AI-driven projects. The course emphasizes applying both traditional and agile methodologies
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and can be customized to meet participants' individual learning goals. Participants manage patients with a wide variety of infectious diseases on both an inpatient and an ambulatory basis. St. Jude
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models (e.g., deep learning, reinforcement learning, probabilistic graphical models) for applications in genomic prediction, GWAS, GS, gene-editing target discovery, and multi-trait selection. Conduct