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Field
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primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or
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Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong
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Abstract: This position focuses on the development of intelligent and autonomous drone systems, integrating AI, edge computing, and digital twin technologies for mission autonomy and predictive
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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the command line. Background in structural biology, molecular modeling, protein dynamics, and understanding of ensembles. Have experience with large-scale computations on compute clusters, bonus points
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and temporal scales. Through this research, you will gain a better mechanistic understanding of these relationships as a basis for predicting future changes related to management decisions and climate
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process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process analytical technology (PAT); process intensification
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imaging, infrared thermography and image-based performance modelling. You will join the Solar Photovoltaics Systems Team at DTU Electro, an internationally recognized research environment focusing