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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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for real online scenarios and to study formal verification methods. The program will involve the study of machine learning tools and the development of simulation systems capable of integrating multiple data
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storage, and organic optoelectronics intelligent and advanced polymers and materials. Project description: The Lithium-ion battery comprises multiple individual units known as "cells." Any deterioration
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will be responsible for programming and maintaining gait exoskeleton systems, developing and implementing real-time control algorithms in C/C++, Python, and Simulink, as well as integrating feedback from
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-cell and spatial-omics research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic
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University of California Agriculture and Natural Resources | Davis, California | United States | 3 days ago
services. Applies advanced software concepts to design, develop, modify, debug, deploy, and evaluate highly complex software solutions. Analyzes existing systems and devises algorithms for new software
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Autonomous System Designer you will design, implement and test algorithms for autonomous decision making on Uncrewed Underwater Vehicles (UUVs) for the Advanced Technology Laboratory (ATL), at ARL
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. The participant may also have the opportunity to be involved with the development of novel algorithms, bioinformatic tools or analytical pipelines that quantify the diversity of RNA viruses that may be deployed in
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) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware