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, particularly artificial neural networks, and deep learning? And you would like to continue your research on clinically relevant topics? If yes, then Maastricht University has a new challenge for you! Postdoc
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your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
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frameworks. L–H/H–L transition physics, pedestal evolution, or core-edge coupling. Analysis and validation using experimental data from tokamak facilities. Machine learning, scientific AI, neural-network
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neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view learning, transfer learning, and data fusion techniques to integrate heterogeneous omics datasets
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on developing novel neural network approaches to predict protein conformational dynamics from fixed protein structures, addressing fundamental challenges in structural biology with broad applications in
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
following areas: High-dimensional probability and concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations
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machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position Requirements: The successful candidate is expected to: Build and evaluate chemical
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concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical
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diverse set of time-dependent forecasting models (e.g., neural network, mechanistic, statistical, and data-driven) to serve as experts within the integrative architecture. (iii) Mixture-of-experts
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learning libraries (such as TensorFlow, PyTorch), along with experience in structural modeling tools (e.g., Vienna, Rosetta, RNAstructure) and graph neural networks or transformers applied to molecular