12 phd-position-computer-science-"Multiple" "NTNU Norwegian University of Science and Technology" PhD positions at SciLifeLab
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program! At Karolinska Institutet, we are announcing the position as DDLS PhD student in Data driven cell and molecular biology. Data driven cell and molecular biology covers research that fundamentally
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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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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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Uppsala University, we are announcing the position as DDLS PhD student in Data driven epidemiology and biology of infection. Data driven epidemiology and biology of infection covers research that will
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that change? Then join us in this unique program! At Karolinska Institutet, we are announcing the position as DDLS PhD student in Data driven epidemiology and biology of infection. Data driven epidemiology and
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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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and career advancement across the globe. DDLS industrial PhD position We are announcing the position of Data-driven life science (DDLS) PhD student in data driven cell and molecular biology. This is an
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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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. The future of life science is data-driven. Will you be part of that change? Then join us in this unique program! Project description This PhD student position is in the research team of Associate Professor
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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