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Field
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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reference. The student will focus primarily on the photonic integration of machine learning methods, contributing equally to the development of ML algorithms in this context. Their work will include
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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Duties and Responsibilities Responsibilities: 1. Conduct research on AI-driven methods, including reinforcement learning and diffusion models, for molecular and antibody design. 2. Develop algorithms, run
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is required, particularly in the development of digital solutions, data processing and integration, computational modelling, or optimization algorithms. Preference will be given to candidates with
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student
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of three-dimensional inference algorithms from object views, based on Generative Networks for Robotics Applications. V - Initial grant duration: 5 months, as long as it doesn't go beyond the end date
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Intelligence and Algorithms – 30%; VII.II- I – In the evaluation of the interview, candidates' performance will be assessed according to the following weights and criteria: - Criterion 1: Knowledge and profile
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carbon calculation tool, including data ingestion, estimation algorithms, and automated reporting. o Build and maintain ontologies/knowledge graphs mapping activities, materials, equipment, emission
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration