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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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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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biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest. Minimum Acceptable Education & Experience
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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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of Pittsburgh, University of Texas Medical Branch and BARDA, aimed at advancing pandemic bio-preparedness through AI-driven forecasting. With advances in machine learning frameworks and emerging accelerator
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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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for interacting with colleagues and stakeholders. Department Specifics Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune