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Field
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of computational biology and bioinformatics; Research and stay current with project related scientific literature; Develop and validate new algorithms and tools to accomplish scientific objectives; Identify and
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to integrate large and complex molecular datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
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Development and Alumni Relations (DAR) supports Johns Hopkins’ focus on research, teaching and patient care, and its role as a national and global leader in higher education. We create and foster
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on available work, funding, and performance. Anticipated Division of Time (30%) Direct research program in AI/ML applications for climate science, including supervising team members, developing novel algorithms
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to join a multidisciplinary team working on the development of energy-efficient, fault-tolerant AI systems resilient to space radiation. This collaborative project spans multiple levels of research
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workforce Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions Gender-friendly environment with multiple actions to attract, develop and retain
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to work across disciplines, with an interest (or willingness to develop expertise) in areas such as machine learning, route planning algorithms, aircraft design and testing, and systems engineering. For a
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to join a multidisciplinary team working on the development of energy-efficient, fault-tolerant AI systems resilient to space radiation. This collaborative project spans multiple levels of research
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
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of multiple geophysical datasets and interpretations, and the development of new concepts and methods to automate the processing of field data in near real-time to provide insights to wildland fire commanders