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: PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field. Strong expertise in machine learning for materials science (e.g., generative models, neural networks, active learning
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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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, leveraging advanced learning analytics, machine learning, and deep learning techniques. The candidate shall work under the supervision of the Principal Investigator (PI) and Co-PIs to conduct academic research
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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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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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languages; A good record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization; Proficient in
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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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