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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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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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chemistry, biochemistry and organic chemistry. More than 100 people, including around 45 PhD students, work at the department. New employees and students are recruited from all over the world and English is
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design. This unique PhD position is a 4-year collaborative
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well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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, and will apply deep learning to integrate the analysis flows. The PhD student will develop the method and apply to numerous in-house samples of environmental sequences, pushing the boundaries of RNA