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related field experience in the analysis of high-dimensional biological or medical datasets, ideally in the context of omics technologies proficiency in R/Bioconductor for statistical computing and analysis
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participation in the establishment of a junior research group on R&D in this field is explicitly desired, as is intensive co-operation with the Faculty of Physics and Astronomy of the Friedrich Schiller
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extraction, sequencing library preparation, Hi-C, ATAC-seq etc.) Experience with bioinformatic analysis of large sequencing data sets Strong statistical skills using R Desirable: Experience with assembly
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/or genomics is required Strong analytical skills as well as broad experience with scripting languages (e.g. Python, R, Bash); knowledge of common bioinformatics software and access to databases
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experience in python and/or R demonstrable experience in multi-omics and/or single cell omics data analysis knowledge of machine learning principles and applications very good interpersonal and communication
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language (R, Python, Matlab, ...) experience with the use of a geoinformation software ability to work in a team, very good communication skills, independent working style and organizational skills very good
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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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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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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