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Field
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Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Expertise in or a strong interest in machine learning and deep learning algorithms. · Excellent communication skills
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scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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our team, as well as a willingness to learn new methods and techniques as the projects evolve. This is a one-year full-time appointment with the potential for extension contingent upon successful
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. Research opportunities will focus on the use of novel modeling tools for hydrology and water resources systems, with an emphasis on machine learning and remote sensing, with a focus on developing detailed
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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in Dr. Shanlin Ke’s lab. The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and
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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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docking and machine learning. Among the key duties of the position are the following: Performs various research and technical operations relative to ongoing investigatory activities of a laboratory; may