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Max Planck Institute for Mathematics in the Sciences | Leipzig, Sachsen | Germany | about 18 hours ago
strong background in mathematics and machine learning, particularly mathematical optimization, polyhedral geometry, algebraic geometry, neural networks, or related areas, and is eager to contribute to high
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-reconstructions and observations, low-order data assimilation, or deep neural networks. A quantification of the impact of mesoscale and submesocale features is also expected. At a later stage, the successful
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characterization of the molecular regulatory networks that underly neural development. Core research of our lab focuses on the role of Bcl11 transcription factors in cortical development (Okuyama et al., Nature
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Schrödinger equations, based on nonlinear approximations such as low-rank tensor decompositions, Gaussian mixtures and neural networks, with a particular focus on the computational costs of reliable solvers
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extensive expertise in electrophysiology to join international research team "Astrocyte-Neuron Networks" lead by Prof. Dr. Cristina García Cáceres at the Institute for Diabetes and Obesity (IDO
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the neural basis of high-dimensional category learning in vision. The project investigates neural mechanisms of category learning at the level of circuits and single cells, utilizing electrophysiology
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neural differentiation paradigms, patient specific iPSCs, (epi-)-genomic approaches (single cell omics, massively parallel reporter assays) and genome and epigenome editing as well as computational
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Postdoc (f/m/d) in Machine Learning for Quantum Computing and Simulation of Quantum Matter / Comp...
) methods to study complex quantum systems relevant to the green energy transition. The focus is developing novel Neural Quantum States, deep learning approaches to design quantum computing (QC) algorithms
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will train a physics-informed neural network (PINN) for fast, precise predictions of pressure, density, and velocity fields. The project also includes producing feed spacer prototypes through 3D printing
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio