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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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will work on projects where research meets real-world challenges. This includes developing soil moisture maps to reduce damage from forest machinery, testing innovative methods to control pests in
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cytometry, FACS, and qPCR for quantifying infection; as well as statistical analysis. You are also likely to use CRISPR/Cas9 technology, CLIP assay, co-immunoprecipitation, and other biochemical methods
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of extremist messages, or the use of social media or AI in politically motivated criminal practices. The dissertation work may be conducted using qualitative, quantitative, or mixed methods, and should connect
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at the same time so special. The originality of the experiments is in the combination of X-ray based scattering and imaging methods to monitor the changes at the particle scale during testing. Research
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experience working with deep learning methods for biomedical applications. Academic and Project Excellence: Evidence of high-quality research work, as demonstrated by academic grades, the merit of prior degree
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use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across the different organelles. Another approach is to use Monte Carlo
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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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to understand the emergence and transformation of the public debate on immigration in Sweden. The Social Network Analysis Group develops and applies novel methods to examine the formation of social ties and the
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to construction processes, policies, or material flows. Familiarity with research or practice at the intersection of building production methods, circular business models, and sustainability transitions. Experience