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This position is embedded in the AIR-MoPSy project (Atmospheric Impact on the R-Mode Positioning System), which supports the development of a terrestrial backup to satellite-based navigation systems. GNSS (Global
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proficency (Python or R, bash) experience with working over an HPC system not required, but beneficial: background on climate, hydrology or geography We expect: the ability to work independently and on your
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Strong publication record A keen and documented interest in the research agenda of the project Experience with analysis of longitudinal data and related data management Proficiency in using Stata and/or R
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and phylogenetic comparative analyses using R or Python Present research findings at scientific meetings and symposia Prepare and contribute to the publication of results in peer-reviewed journals Your
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data using MEFISTO. Nature Methods (2022) Kleshchevnikov, Vitalii, et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nature Biotechnology (2022) Argelaguet, R., et al. Multi
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(e.g. Julia, Python, R) are a requirement Good programming skills in a low level language (e.g. C/C++, Fortran) will be considered advantageous Our offer A vibrant research community in an open, diverse
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data science tools, especially Python or R Proven ability to work collaboratively in interdisciplinary and international research settings Strong skills in scientific project management Excellent written
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publication record #excellent programming skills in Python or at least one other scientific programming language (e.g. FORTRAN, C, Matlab, R) #good knowledge of English (written and oral) #high degree
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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to submit the dissertation after 3 years and 9 months of research. Desired requirements specific to this project include: experience with a range of relevant computer programming languages such as Python, R