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). Contribute to sport business and operations analytics projects as needed (e.g., ticketing, fan engagement, and scheduling). Build and maintain data pipelines and models using R, Python, SQL, and cloud
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analytical and mathematical skills, including proficiency in quantitative modeling, data analysis, and scientific computing (e.g., R, Python). Strong written and verbal communication skills in English. *for
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Maintain detailed records of results and prepares written reports acceptable to the Principal Investigator and funding agencies Other duties as assigned Unit URL https://uiexperimentalforest.org/ Position
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Independent way of working Basic programming skills (Python) advantageous Very good knowledge of German or English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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various data analysis tasks. Your work will focus on carrying out data preprocessing, data wrangling, and carrying out analyses using R (and sometimes Python). Example projects you will be working
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such as R, SAS, ArcGIS, SQL, Python and AI tools. Conducts geospatial and epidemiologic analyses relevant to the catchment area to assess cancer outcomes, spatial patterns, temporal trends, and disparities
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developability assessment tools such as aggrescan, AbImmPred etc. - Strong knowledge of different machine learning architectures and training techniques is essential. - Proficiency with programming in Python and
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Group or Departmental Website: https://plevritislab.stanford.edu/ (link is external) https://ccsb.stanford.edu/ (link is external) How to Submit Application Materials: Go to: https
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Artifact Repository: Artifactory Network: SSH, SCP, FTP, HTTP(S), TCP/IP, STIG compliance, firewall/iptables setup. Scripting: Bash, Perl, Powershell, YAML, Python Operating System: LINUX (Redhat, Ubuntu
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publications, conference presentations, and robust coding practices, including version control and reproducible data pipelines. Proficiency in Python, ML frameworks such as TensorFlow or PyTorch, statistical