Develop informatics software and analysis tools for machine learning analyses of genomic, clinical, and imaging datasets. (30%)
Provide documentation and user support, enabling computational researchers to access and use informatics software. (25%)
Maintain well-curated, highly structured, transparent omics, imaging, or clinical data resources and databases suitable for machine learning. (20%)
Develop software tools to integrate bioinformatics and machine learning software applications with data resources. (20%)
Establish and maintain standards for structured software engineering, including requirements, design, code, test, quality, configuration & release management, and project management. (5%)
Requirements & Skills:
Expertise in the following areas: (1) software development, (2) analysis pipeline development, and (3) machine learning analyses. Expertise using software development and analysis skills in a scientific discipline is preferred.
Experience using open-source software libraries for traditional machine learning and deep learning. Experience using commercial machine learning libraries, experiment tracking software, visualization and reporting software, and scaling libraries is preferred.
Strong knowledge of the Python programming language plus experience in other programming languages such as R, Perl, C#, and Java. Knowledge of data structures, runtime analyses, and continuous integration preferred.
Experience developing web-based and/or scientific software that includes several components and/or libraries, including a database. Experience developing open-source software is preferred.
Enjoys working in a multidisciplinary and collaborative environment.
Minimum of bachelor’s degree with two (2) years of software development.
Preference given to software development experience in biomedical data analyses and machine learning applications.
