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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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, quantification, and data analysis, including statistics. Variations of liquid extraction-based techniques, based on nano-DESI and electrospray ionization, will be developed further and coupled to modern mass
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skills (e.g., programming, statistics) or a willingness to develop them will be considered particularly important for this project. Admission Regulations for Doctoral Studies at Stockholm University. About
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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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the molecular level. While structural predictions using deep learning methods like AlphaFold have revolutionized our understanding of sequence dependent molecular structure, we currently have much more limited
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, structural biology, and NMR spectroscopy. The successful candidates will become a part of an international multidisciplinary environment and will receive ample opportunities for learning, collaboration and