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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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at the intersection of computational biophysics, AI/ML modelling, and biophysics/chemistry-driven approaches to understanding and developing therapeutic lipid nanoparticles. Focus areas of the position Chemistry
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and motivated PhD student to join an interdisciplinary project that combines computational biology, spatial transcriptomics, and tumor modeling to understand how the aggressive brain tumor glioblastoma
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for computational protein design, but also for an array of other applications related to modeling and understanding proteins and their behavior. The heart of the project will be the development and refinement
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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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 to human health
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model