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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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and psychometric instruments is mandatory. Preference will be given to applicants with knowledge of analyzing quantitative research data using advanced statistical tools (e.g., MPlus, R). Applicants
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for This Position" button located below the Contact Information. Contact Information Contact:Jan R Wessel - jan-wessel@uiowa.edu Clas-Psychological Brain Sci Psychological and Brain Sciences Building 340 Iowa
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minimum using a processor-in-the-loop setup). contributing to the roadmapping, definition and implementation of R&D studies dedicated to the use of machinelearning techniques for the development of GNC
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programming language (R, Python, or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform analytical reasoning to extract biological insights from data
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with a strong background in molecular virology, next-generation sequencing, Bayesian analysis, phylogenetic analysis, statistical genetics, and the ability to use R and/or UNIX/command line applications
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with large-scale human omics (preferably related to neurodegeneration) studies is expected. Preferred Qualifications: Skilled in at least one programming language (R, Python or Perl) and experience
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spatial transcriptomic data using R or Python; interprets findings in the context of transplant immunobiology. Establishes new research protocols and procedures: Develops and optimizes protocols
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analysis using data software is required (e.g., SAS, STATA, R, etc.). Qualifications: Doctorate degree in Epidemiology (or related field) from an accredited university by the start date required. Knowledge
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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