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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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++, or related languages Experience with high-performance computing or scalable algorithms Interest in interdisciplinary research spanning genomics and evolutionary biology Modes of Work The position is on-site in
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University of Massachusetts Chan Medical School | Worcester, Massachusetts | United States | about 2 months ago
biology as a high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain
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graph-based algorithms for genetic data. The specific project involves understanding the unique evolutionary histories of diverse populations, both in humans and other species. The research specialist
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environments, scripting languages for handling large-scale genomic data, and learning how to apply programming languages to implement complex computational models and algorithms. Learning objectives will include
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Linux environments, scripting languages for handling large-scale genomic data, and learning how to apply programming languages to implement complex computational models and algorithms. Learning objectives
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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors