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). - Apply image processing, segmentation, and normalization techniques using Python-based libraries. - Ensure pipelines are reproducible and version-controlled to meet analytic standards. Feature Extraction
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interoperability frameworks (e.g., OMOP, FHIR) Familiarity with Python and clinical data integration tools Strong organizational skills and attention to reproducibility and versioning Experience collaborating with
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, pharmacology, engineering, bioinformatics, or a related field. Preferred: Prior pharmacokinetic modeling or machine learning experience using software such as R, Python, MATLAB, GastroPlus, PK-Sim, Phoenix
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field and three years of experience. Preferred: Experience building and maintaining ML/AI pipelines for multimodal biomedical data Proficiency in Python and deep learning frameworks such as PyTorch
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, Freesurfer, UNIX/LINUX computational environments and/or programming skills (MATLAB, R, C++; JAVA, Python) is desirable, but not required. Applicants who have experience in the study of children (especially
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in such a way as to be accessible by lay and professional audiences Technology • Using R, SAS, Python, SPSS, Tableau, and/or other database/analytical software platforms at an intermediate level of
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mathematics education. Experience with coding languages for data management and analysis (e.g., R, Python, SQL) Experience with assessment and survey development. Experience with testing validity and
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software such as Docker. • Leverage Python, SQL, and Docker to test code in development environments and deploy processes to a production environment. • Design, implement, and manage data storage and
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/Python Prior experience in genetic or genomic data analysis Special Instructions to Applicants: To be considered, applicants must upload a CV, a letter of intent, including a brief summary of past and
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(at least 4 years) with server-side languages, such as Python, C#, PHP, Perl, Java, and Node.js Experience (at least 4 years) with HTML, CSS and JavaScript Experience (at least 4 years) with Object-oriented