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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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disciplines. • Previous experience in microbiology/bioinformatics/bacterial genetics would be desirable. • Knowledge of a scripting language and R is a plus. • Excellent English communication skills (written
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Knowledge in deep learning Experience with object detection algorithms, e.g. Yolo or Faster R-CNN Plus: first experience with 3D object detection. What you can expect Very nice supervisors, a good atmosphere
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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and competency conducting literature reviews in the social sciences (economics, political science, sociology, etc.) knowledge of R and/or Python for conducting econometric analysis or text analysis
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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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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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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
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R documented excellent and intuitive graphical presentation of data analyses for presentation and publication excellent English language skills (speaking and writing) comprehensive presentation
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chronometabolic research Analysis and quantification of circadian rhythms by rhythm analysis software (Cosinor, JTC cycle, R etc.) Rhythm analysis in human 24-hour time series data and omics data Writing