69 application-programming-android-"Prof" Postdoctoral positions in United Arab Emirates
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kyriakopoulos seeks
-
Reality to elicit users’ preferences for innovative transport systems. Applicants with a background in behavioral analysis and mathematical modelling are encouraged to apply. Terms of employment include
-
. 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
-
they plan to contribute to create interdisciplinary connections within the research areas of the center. Questions regarding specifi cs for this position may be directed to Prof. Hisham Sati hsati@nyu.edu
-
efforts relevant to wireless technologies, in coordination with academic and industrial collaborators. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering
-
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
-
. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include: Strong background in communication theory, signal processing
-
. To be considered, all applicants must submit Cover letter Curriculum vitae with complete publication list BSc, MSc and PhD transcripts Research statement elaborating how you plan to contribute
-
developing new treatments and diagnostics for cardiovascular, neurologic, and metabolic diseases. The successful applicant will join a number of fascinating projects on engineering novel approaches to modulate
-
the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation