-
understanding of data evaluation, modeling, and interpretation of complex datasets Ability to work independently as well as collaboratively in an interdisciplinary and international research environment Very good
-
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
-
methods for their bottlenecks, these steps will then be replaced or supplemented with ML-based surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs
-
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
-
geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
-
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
-
? Set up a network model to reproduce the main results and provide potential neuronal mechanisms. Existing recordings with optogenetic inactivation could be leveraged to causally verify or reject important
-
or spike correlation patterns limited to local neural circuits or span across brain regions? Set up a network model to reproduce the main results and provide potential neuronal mechanisms. Existing
-
, or machine-learning frameworks is an asset Strong analytical skills with a solid understanding of data evaluation, modeling, and interpretation of complex datasets Ability to work independently as
-
, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow