67 phd-in-computational-mechanics-"KHALIFA-UNIVERSITY" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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technologies. The candidate should have a PhD or MSc in Computer Science or a closely related field (BSc holders will be considered in justified cases). Relevant background and skills include: Experimental
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experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering Mechanics, Civil Engineering, or Mechanical Engineering. Applicants are expected to demonstrate research
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independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural
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experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants
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United Arab Emirates Application Deadline 1 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
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. Safe and Certified Control for manipulation: Designing control algorithms that ensure passivity, Lyapunov stability, and safety for human-robot collaboration. Qualifications: Applicants must have a PhD
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, organization of scientific workshops, and attendance at conferences. Key qualifications include a PhD in a relevant field, expertise in AI/ML (e.g., PyTorch, TensorFlow, Python), interest in materials
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learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems