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develop transformative therapies for glioblastoma (GBM) by understanding the disease on its own biological terms, within the complex context of the human central nervous system. We are entering an exciting
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developing novel methodologies or adapting existing techniques to new applications Analyse complex datasets using appropriate computational and statistical tools, and interpret results in the context
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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institutes working at the interface of technology and life sciences. This is a unique opportunity to contribute to a research programme that is technique-agnostic, impact-driven, and unafraid to push
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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topics include, for example: Quantum information in quantum gravity Relativistic Quantum Information Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g
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. Qualifications: PhD in Molecular Biology, Biomedicine, Human Physiology, Computational Systems Biology or similar fields. Proven expertise in LC/MS based metabolomics and/or bioinformatic analyses of complex omics
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Postdoctoral Research Scholar in Machine Learning and Computational Genomics Department of Epidemiology, School of Public Health, University of Pittsburgh The Department of Epidemiology
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The Department of Molecular Biology and Genetics at Aarhus University is a vibrant and exciting interdisciplinary research environment. The department is located in a newly renovated laboratory complex with well
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A postdoctoral research associate position is available with Dr. Christoph Gorgulla. This project aims to advance computational drug discovery by developing and applying innovative computational