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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches
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» Computer engineering Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Sep 2026 - 23:59 (Europe/Athens) Country Cyprus Type of Contract To be
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-order modelling, surrogate models, and machine-learning methods such as neural networks. Control design for flexible reactor operation. Develop advanced control strategies that enable safe and efficient
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collaborations with biophysics laboratories. The project lies at the intersection of artificial intelligence, machine learning, computational physics, and molecular biology, and aims to contribute new
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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
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following areas: Robotics and Autonomous Systems Artificial Intelligence and Machine Learning Wireless Communication Systems Ultra-Wideband (UWB) Technologies Industrial Automation and Industry 5.0 Industrial
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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, cryo-electron microscopy (cryo-EM), cryo-EM-based polyclonal serology (cryo-EMPEM), molecular dynamics simulations, machine learning, and structural biology to define epitopes and engineer improved
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
additional days per year, including your birthday Minimum Requirements: PhD in Engineering Experience in Machine Learning, Deep Learning, reduced-order modeling, or physics-informed models Knowledge