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particular, we aim to develop a neural network architecture that will allow us to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design
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planning and execution architecture for information-driven experiment steering (closed-loop control) Work in an interdisciplinary team of engineers, computer scientists, and life scientists Present your work
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only
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environments Design and implement reinforcement learning algorithms for control and manipulation, first in simulation and later on real experimental setups Refine a real-time planning and execution architecture