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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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research. You are expected to have significant background and interest in Suspect Screening or Non-target Analysis, Environmental Organic Chemistry, Analytical Chemistry, Environmental Microbiology
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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scan data is desired Familiarity with analytical tools such as R or Python for statistical and phylogenetic comparative analyses Experience with scientific writing and publishing in peer-reviewed
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focus is demonstrating how predictive analytics can improve maintenance and production planning. By comparing data-driven and traditional methods, the project will highlight the tangible benefits
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that addresses large and complex issues and develops new analytical tools. That’s why the WIFORCE Research School, part of the Wallenberg Initiatives in Forest Research (https://www.slu.se/WIFORCE/en
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(including email addresses) of two referees; 4. At least one example of written work (in English, including some data analysis) that demonstrates your analytical and writing skills in a social science
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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of great ape communication to identify evolutionary trends and simulate dynamics that might explain the evolution of common ground in humans. For more information see the following representative articles
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://kdvi.uva.nl/research/discrete-mathematics-and-quantum-information/discrete-mathematics-and-quantum-information.html#Academic-Staff Silke Henkes -- https://www.universiteitleiden.nl/en/science/physics/biological