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Experience1 - 4 Additional Information Eligibility criteria DFT with periodic boundary conditions applied to materials; development and implementation of codes or algorithms for materials modelling, ideally in
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Algorithms for Agro-industrial, Health, and Environmental Sustainability, within the FAPESP Center for Research and Innovation on Smart and Quantum Materials (CRISQuaM). The project aim to develop quantum
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georeferenced data on pest outbreaks. The Scholar will use these data in collaboration with computer scientists to develop machine learning algorithms for the detection and management of biotic stress. The crops
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systems, understand the design and development decisions that propagate social biases, and develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
Requisition Id 15685 Overview: The Center for Nanophase Materials Sciences (CNMS) is seeking a Postdoctoral Research Associate to support research directed towards developing novel AI/ML algorithms
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wafers are processed across hundreds or even thousands of manufacturing tools following highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 19 hours ago
Lidar and the Roscoe upper troposphere/lower stratosphere lidar). Additional projects include the development of machine learning and advanced data processing algorithms, and participation in upcoming
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-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments
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allows the successful applicant to choose a flexible balance between advanced machine learning method development and exciting applications on molecular data, including biomedicine and drug discovery