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years of postdoctoral research experience is preferred. Strong background in big data analytics, machine learning, and multi-omics. Strong track record of high-quality research, demonstrated by
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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expected to teach one course per semester, with no additional research or service obligations to the department, allowing the scholar ample time to pursue their own research agenda. Candidates must have
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in peer-reviewed journals and present findings at scientific conferences. Teach and develop curriculum in AI, bioinformatics, and biomedical data science. Mentor students, trainees, and junior
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environments Interest in industrial monitoring systems, smart sensors, and sustainable manufacturing Experience with sensor data processing or instrumentation systems Knowledge of machine learning or anomaly
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· An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international
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?s current research areas include Clean Manufacturing and Advanced Materials, Energy Storage and Transportation, Radiopharmaceutical Therapies, and Circular Bioeconomy Systems. To learn more about UT
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yourself. Independent researcher: You are interested in mixed-methods research and are willing to learn a new research methods and take responsibility in its execution. Curious and open-minded: You have
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, individualized education. Faculty are committed to creating a student-centered learning community that embraces multiple viewpoints. It is a department in which learning, research, and professional activity inform
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- Quantum Reinforcement Learning, quantum computing, QKD - quantum key distribution, entanglement distribution System-level design and optimization AI & Intelligence: Agentic AI, Edge AI, information