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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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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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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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-omics analyses, we have been granted funding from DDLS in the field of data-driven precision medicine and diagnostics (see below). The project is titled: Causes and consequences of whole-body composition
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. The project revolves around developing Traident – a new method to resolve the species origins and compositions of complex RNA sequence data. This will extend Kraken2 with analyses of ribosomal RNA and microRNA
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-assembly on a structural level, and correlate this with in vitro functional activity. At AstraZeneca, the student will be integrated into the Data Science and Modelling department within the Pharmaceutical
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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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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
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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