932 machine-learning "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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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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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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to oversee research activities outlined in NSF Grant 2520154 “Understanding Expectation-Driven Learning in Early Childhood: An Experimental and Computational Investigation,” under the supervision of Dr. Kimele
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active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some
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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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Universe (KMI)-PD [#31232, KMI-2025-2] Position Title: Position Type: Postdoctoral Position Location: Nagoya, Aichi 464-8602, Japan [map ] Subject Area: AI/Machine Learning / Astronomy Appl Deadline: 2025
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-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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, France [map ] Subject Areas: Machine Learning / Machine Learning Mathematics Statistics Statistical Physics Probability Appl Deadline: 2025/12/20 11:59PM (posted 2025/11/25, listed until 2026/05/25
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intelligence (including machine learning). Desired Qualifications Publications in health sciences and biomedical journals. Demonstrable interdisciplinary research experience. Deep understanding of machine