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Uppsala University, Department of Information Technology In this project we will conduct research towards trustworthy and robust use of neural networks with applications in epidemics. We consider a
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, which is the overwhelming camera technology of today; machine learning with deep neural networks. More details can be found here . The Department of Mathematics at KTH offers a high-class, active research
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. We are seeking a motivated postdoctoral researcher to study how neural activity influences 3D genomics
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neural activity influences 3D genomics, the chromatin landscape, and cellular plasticity in glioblastoma. The position is a full-time, two-year appointment. The postdoctoral position is funded by a
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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machine learning models in simple, standalone devices that are capable of advanced processing. Building on our work on solution-based neuromorphic classifiers (https://doi.org/10.1002/advs.202207023
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analysis in medicine. Experience of software version control with Git, typesetting with LaTeX, use of Linux computers; Experience with graph-based methods, and graph convolutional/neural networks; Experience
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, innovative technologies for biomass conversion, neural network systems, and artificial intelligence for more efficient mathematical and computational approaches. Subject description The work focuses on