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: Development of ML-based tools for analysis and engineering protein dynamics PhD enrolment: Czech Technical University in Prague DC14: Machine learning for Empirical Valence Bond (EVB) simulations to engineer
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students who are prepared for a lifetime of learning and rewarding work. Candidates should hold a PhD or master’s degree in electrical and computer engineering or related fields and should be comfortable
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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the supervision of Dr. Warda Ashraf. Required Qualifications PhD in Civil Engineering, Materials Science, or related field. Preferred Qualifications Research experience with alternative cement chemistry and/or
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Classification Title: Assistant/Associate/Full Instructional Professor Classification Minimum Requirements: PhD in engineering or a closely related discipline. Job Description: The Department
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flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures for cyber-physical energy systems AI-based energy system modeling, simulation, and optimization Secure and
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are of particular interest and thus are strongly encouraged to apply. Detailed Position Information The Department of Aerospace Engineering and Mechanics (AEM: https://aem.eng.ua.edu ) and the Lee J. Styslinger Jr
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Website https://www.academictransfer.com/en/jobs/358703/phd-in-scalable-safe-ai-for-sem… Requirements Specific Requirements A master’s degree AI, Machine Learning, Data Science, Computer Science or a
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systems, manufacturing systems, supply chain systems, and transportation systems. Our faculty performs methodological research in data analytics, machine learning, human systems engineering, optimization
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network management. You will have a good first degree in physics, electrical and electronic engineering, computer engineering/science, or another relevant subject, and a PhD or equivalent experience in