Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
or population genetics theory Evidence of technical skills and interest (e.g., writing code, using git, HPC experience) Understanding of basic statistical methods Demonstrated ability to review and synthesize
-
interest (e.g., writing code, using git, HPC experience) Understanding of basic statistical methods Demonstrated ability to review and synthesize literature into scientific concepts About us The Department
-
)statistics, (applied) mathematics, computer science, or a related field; candidates from other fields with strong programming/coding skills (see below) are also encouraged to apply. Proficient in at least one
-
. Meritorious A degree in bioinformatics, computational biology, (bio)statistics, (applied) mathematics, computer science, or a related field; candidates from other fields with strong programming/coding skills
-
, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
-
. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ Background and description of tasks Our group develops new single-cell multiomic methods to characterize microbial
-
epidemiology and biology of infection. For more information, please visit: https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will you be part of that change
-
strategic research areas: cell and molecular biology; evolution and biodiversity; precision medicine and diagnostics; and epidemiology and biology of infection. For more information, please visit: https
-
: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven
-
. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ Data driven epidemiology and biology of infection cover research that will transform our understanding