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Research Associate. The Goodwill Computer Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning
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. Essential qualifications: PhD in Computer Science, Robotics, Machine Learning, or related fields. Programming skills in Python/C++ and experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX). Strong
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(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
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skills Desirable criteria Experience of atomistic modelling of ferroelectric materials Experience in development and application of machine learned potentials * Please note that this is a PhD level role
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 5 hours ago
Candidates should have a PhD in physics or a related field, and will be evaluated on their academic credentials and their prior research record. Preferred Qualifications Experience with machine learning (ML
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of atomistic modelling of ferroelectric materials 2. Experience in development and application of machine learned potentials * Please note that this is a PhD level role but candidates who have submitted
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terms of research and education, covering all aspects of computer science, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering
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) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world robotic systems, including dual-arm manipulators and soft robotic grippers These positions are part
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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in