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flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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propagation, electromagnetics, optimization, machine learning, and networking. Strong documented experience in these areas is commendable, particularly by having published your work. Candidates should have an
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, electromagnetics, optimization, machine learning, and networking. Strong documented experience in these areas is commendable, particularly by having published your work. Candidates should have an excellent mastering
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automata, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree
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, which provides a fantastic opportunity to learn how to run challenging development projects. Qualifications We are looking for analytic and motivated colleagues that can perform advanced research, both
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opportunity to learn how to run challenging development projects. Qualifications We are looking for analytic and motivated colleagues that can perform advanced research, both independently and in cooperation
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look forward to receiving your application! At the intersection between AI and single atoms. Your work assignments We are looking for a PhD student with a background in machine and deep learning with
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multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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at cell membranes; Apply machine-learning models trained on simulation data to study how lipid composition and genetic variation influence the conformational and phase properties of membrane-associated
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and 3D electromagnetic simulations is considered a significant advantage. Your workplace You will be working at the Division of Electronics and Computer Engineering (ELDA), which conducts teaching and