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, Experimental Research Methods, Explainable AI, Global Strategic Planning, Graph Neural Network (GNN), Hypothesis Generation, Inclusive Practices, Integration Services, Interpersonal Communication, Knowledge
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Quantitative MRI is a PICNIK with Physics-Informed data Consistent Neural Implicit K-space
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electrochemical methods Experience with a variety of printing methods for electronics applications A thorough understanding of machine learning models and experience building and evaluating artificial neural
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-supervised tasks (i.e. k-nearest neighbours, Decision Trees, Neural Networks, Logistic Regression, Gradient Boosting, Self-Organizing Maps); Advanced knowledge of Python programming, namely numpy, pandas
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters of strongest influence on the target properties. Moreover, the obtained data will be fed
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neural network or other machine learning method are available and should be evaluated before implementation. The simulator can then be used to study the nocivity of natural and synthetic ground motion
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of curricular units 3 - Knowledge of algorithms and artificial intelligence models applied to the prediction of student dropout (e.g., GPT, decision trees, k-NN, neural networks) 4 - Knowledge of techniques and
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conducting experiments for training and evaluating deep neural networks Knowledge of multi-modal learning, transfer learning, transformers, or self-supervised learning Experience in dealing with large medical
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Matlab, Python, C++ or other relevant language and experience in deep neural networks. Experience and demonstrable expert knowledge in one or more or the following areas: deep learning; graph neural