Sort by
Refine Your Search
-
topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
-
the Division of Engineering, New York University Abu Dhabi, is seeking a highly motivated Postdoctoral Associate to advance cutting-edge research in machine learning (ML). Our lab explores the intersection
-
research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
-
or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
-
. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval
-
(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
-
collaboration. Qualifications: Applicants must have a PhD in Robotics, Control Engineering, Machine Learning, AI, Mechanical or Electrical Engineering, or a closely related field. Strong focus on robot
-
must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven materials discovery, machine learning applications for materials, or generative AI
-
motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
-
emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless