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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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Excellent communication and writing skills Certifications/Licenses Required Knowledge, Skills, and Abilities Preferred Qualifications Experience handling very large datasets Knowledge of R and Python, and
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will work with a multidisciplinary team of simulation, design, and technology authorities, and should have a clear passion for R&D and a commitment to fostering team growth. Job Duties and
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in genomics, genetics, and statistical analyses. Experience with transcriptomic and epigenomic data analysis. Proficiency in programming languages, such as R and Python, for data analysis and
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technologies and methodologies, and Geographic Information Systems software (e.g., ArcGIS, QGIS), Python, and Matlab is required. Knowledge of other programming languages (e.g., C, C++, R, Javascript) is
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judged from published papers or publicly available (e.g., arXived) preprints, will be given priority. Strong programming skills in R/Python/MATLAB with some knowledge of C/C++ will be preferred. Prior
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design, statistical sampling and analysis of large, multi-taxa biodiversity datasets. Expertise in landscape-level biodiversity and production analyses using R, QGIS, Google Earth Engine. Extensive
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applicants will have:*Expertise conducting spatial and statistical analyses*Experience with scientific computer programming in R and Python*Formal training or experience applying quantitative and spatial
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, R and/or Python. a scientific mindset, inquisitive personality, team player, and the capacity to work independently; In our international working environment, there is an increasing amount
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. At the same time, the high rediscovery rate of antibiotics and limited commercial incentives frustrate antibiotic R&D. The co-occurring problems of AMR and nearly empty discovery pipelines form an impending