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Field
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, Computational Biology, Bioinformatics, or a closely related discipline. Demonstrated experience programming in Python or other major programming languages. Proven experience working in Linux environments
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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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and statistical skills, with proficiency in R or Python Experience working with longitudinal data, infectious disease epidemiology, or high-dimensional datasets Demonstrated track record of peer
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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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AI and machine learning methods applied to cancer genomics. Proficiency in at least one modern programming language. Experience with a scientific programming environment, such as python or R, is
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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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data architectures and tools for automating data analysis. Relevant software platforms include Matlab and Python. Develop physics-based computational models (e.g., finite element analysis) to complement
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developing and teaching spatial methods, especially desktop GIS, R, and Python strongly preferred. Desirable Qualifications: Interest/experience in spatial AI approaches. Comfort with research project
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experiment codebases (prefer Python). Apply causal inference and discovery frameworks to clinical questions. Translate proposed methods and frameworks into real-world clinical workflows. Contribute to grant
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peer-reviewed publications Primary Platforms May Include ArcGIS Pro CityEngine Python-based geospatial processing ecosystems Cesium and 3D Tiles streaming architectures Generative AI Integration