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the national Data-Driven Life Science (DDLS) program. About the position and the project As an industrial PhD student, you will be employed by the startup company PredictMe AB while being formally enrolled as a
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
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will be affiliated with the national DDLS program, through which you will have access to computing resources, the national DDLS research school, and other training and networking opportunities throughout
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. Experience in deep learning, computer vision, or neural network development. Experience with live-cell microscopy, fluorescence microscopy, or analysis of 3D/4D image data. Experience in cell biological
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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. The research environment is highly collaborative and interdisciplinary, with close links to national and international networks and consortia. The Data-Driven Life Science Research School Data-driven life
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epidemiology and biology of infection, which is a fully funded, four-year PhD student position. Data-driven life science Research School Data-driven life science (DDLS) uses data, computational methods, and
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks