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Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills, Training/Education
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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, engineering, finance, and health. Key Responsibilities: To perform the pioneer research in AI for climate transformation. To further develop data-driven and machine learning tasks for fighting climate changes
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looking for your next challenge? Do you have a background in machine learning or fluid dynamics and an interest in applying your skills to understand the dynamics of Earth’s fluid core and space-weather
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storage materials, and employing machine learning and high throughput for the discovery of new electrode materials and electrolyte systems. 1. Holds a PhD degree in chemical engineering, chemistry
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storage materials, and employing machine learning and high throughput for the discovery of new electrode materials and electrolyte systems. 1. Holds a PhD degree in chemical engineering, chemistry
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storage materials, and employing machine learning and high throughput for the discovery of new electrode materials and electrolyte systems. 1. Holds a PhD degree in chemical engineering, chemistry
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. Qualifications/Requirements Qualifications / Discipline: - PhD from a reputable institution in Physics, Bio-imaging, Computer Science, or a scientific domain closely related to Machine Learning. - The candidate
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written and verbal communication skills regarding research results. Preferred Qualifications: Experience with deep/graph neural networks and active involvement in data science and machine learning projects