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Field
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new quantitative methods. Proficient programming and data-wrangling skills (e.g., R, Python) for building analysis pipelines on complex, multi-wave datasets. A track record of first-author scholarly
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proficiency in multiple programming languages such as Python/R, with experience in computational analysis of omics datasets. Experience with AI/ML algorithms and prediction model development. Familiarity with
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analysis skills (e.g., Python, MATLAB, LabVIEW). PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”. If you do not already have educational
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analyzing environmental DNA metabarcoding datasets, Use of common bioinformatic pipelines such as QIIME2 and DADA2, Experience in python and R programming languages, Co-authorship of peer-reviewed
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: Training and hands-on experience in epidemiologic and quantitative data analysis Experience with statistical software such as SAS, R, Stata, or Python Experience analyzing observational, survey, electronic
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, or job experience. Proficiency in programming (Python, Julia) (provide evidence with specific examples). Experience with statistical modelling and experimental design. Ability to work in a
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assistants • Write scientific publications and present findings Required Qualifications • MA in computational social science, digital humanities, computer science, or related field • Python proficiency
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, computational modeling, computer vision, natural language processing, or related AI-based methods. Strong programming skills, preferably in Python. Experience working with complex, multimodal datasets and
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. Excellent proficiency in the following areas is preferred: 1. Microsoft Office Applications, particularly MS Word, Excel, Powerpoint 2. Experience in R, Python The successful applicant is expected to possess
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awarded within 3 years in business administration, computer science, information systems, data science, or a related discipline. Programming & Data Skills: Strong proficiency in Python (e.g., NumPy, Pandas