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mechanical activity at the same time. In this context, the use of mathematical models and machine learning methods can be relevant to integrate physiological knowledge in data analysis and to analyze
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research colleagues, and to learn about the larger context of my research and the research project. Offer: The aim of this PhD research is to optimize acoustic metasurfaces of finite size using machine
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methods, including clustering, time-series analysis, and spectral libraries. Strong computer programming skills in Python, R, or equivalent. Good problem-solving skills; attention to detail; ability
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with interests in molecular simulations, machine learning, and statistical mechanics for research opportunities in: • Development of data-driven schemes for the discovery of slow degrees of freedom
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concepts such as distributed cognition, edge computing, machine learning, formal ontologies, unplugged artificial intelligence, frugal computing... Smart Villages (a rural version of the Smart City) and
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of research in the field of Socio-Economic Networks Analysis. Combination of skills in Machine Learning, Multi-Agent Systems, Game Theory, Decision Theory, Dynamical Systems and/or related domains
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stage, the research project consists in the training of the developed scoring function using a benchmark dataset of protein/ligand complexes associated to experimental binding constants. Machine learning
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statistics Excellent background in statistical/machine learning Experience in computer vision is a plus Strong motivation for medical and societal applications of computational methods Knowledge of biology and
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a development strategy focusing on machine learning, data science modelling and artificial intelligence applied to the epidemiological prediction of future pandemics, the development of new models
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or oceanography. Research background should demonstrate competence -- or at least a clear and strong interest -- in artificial intelligence and machine learning to be applied in the field of environmental sciences