Reference #: 1007822SHIFT:Day (United States of America)

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　　A Brief OverviewThe Bioinformatics Scientist I position is an entry level position for a non-PhD level professional. The focus of the position is development, maintenance, and evolution of the tools that support management and analysis of genomic, proteomic, and other complex molecular data types. This includes the support of internal bioinformatics software, implementation and modifications of existing algorithms, and execution of routine tasks of limited complexity within the general area of bioinformatics analysis. The position allows for a wide variety of activities described within the job responsibilities and encompasses positions within both research and clinical environments. All activities occur with a moderate to high degree of supervision and the individual will rely on a high degree of peer-to-peer mentorship. The Bioinformatics Scientist I is primarily focused on the support of higher level bioinformatics personnel but may have minor direct interaction with collaborators and designees to resolve primarily technical issues and solutions.

　　What you will doPre-Analysis (40%): Contributes to the maintenance and development of bioinformatics tool portfolio by developing knowledge of internally developed systems, open-source programs, and commercial applications. Provides efficient data management support.Works with bioinformatics group members to develop functioning pipelines upstream of customized analysis workflows.Maintains pipelines by staying current with evolving algorithms and standards and incorporating into pipeline.Executes robust development testing for commonly used applications such as data processing pipelines.Optimizes performance of applications by working with scientific computing and information systems groups to optimize hardware/software parameters.Defines and prioritizes requirements for pipeline development over time to incorporate new technologies and platforms via functional communication with bioinformatics group members and bioinformatics end users.Identifies appropriate open-source and commercial products that serve needs of pipeline and/or customized analyses of end users.Implements and maintains commercial and open-source software for common bioinformatics and genomics data analysis.Implements, updates and maintains locally stored data resources required for various analysis tasks.Provides ad hoc support and one-on-one and group-based training on key bioinformatics software, features, and workflows.Provides efficient data management support including file transfers, data formatting and manipulation, and basic integration of data from a variety of experimental and reference resources.Develops and maintains working relationship with data providers such as sequencing cores within CHOP and infrastructure groups such as information systems.Continually keeps abreast of evolving data eneration platform fundamentals, file-specific information representation, and strategic application of code base to optimize value of data.Maintains working knowledge of available commercial and openly accessible knowledge bases as they apply to bioinformatics analysis.Coding (30%): Codes and generally supports both ad hoc, single task applications and larger pipeline applications that may combine multiple 3rd party and internally developed applications for genomics/proteomics/other complex data types and projects.Implements, maintains, and regularly contributes to formal and bioinformatics group-centralized code management system.Adopts appropriate forking and other strategies for robust code development. Apply to general bioinformatics group code base.Adopts best practices for code development consistent with larger bioinformatics group. This includes choice of language based on the type of solution being developed, the likely life cycle and downstream usage of the resulting application, and integration with other systems.Ensures that all routinely used tools (e.g. those included in shared analysis pipelines) are versioned and managed through a source control system.Ensures that configuration files that provide parameters to algorithms and analysis software are versioned and managed through a source control system.Develops and implements automated data-driven testing processes that test reproducibility of results between versions of pipeline software.Develops and implements automated deployment processes that build and configure systems from source control repositories, eliminating the need to manually modify configuration files.Regularly documents code, troubleshoot, and provide training when necessary.Data Analysis (10%): Analyzes data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data under supervision from mentors and peers.Develops robust analysis plans under supervision.Incorporates QA/QC in analysis workflows.Delivers analytical endpoints such as feature identification, annotation, characterization, prioritization, etc.Reports results using, primarily, spreadsheets and, secondarily, abstracted materials such as slides and visuals.Collaboration (10%): Works with both bioinformatics group members and end users/clients to understand specific needs in bioinformatics and end user-specific domains.Attends group and team meetings and contributes primarily factual information regarding processes and approach.Defers to mentors and peers in establishing relationships, but works within boundaries to accomplish analytical goals.Academic Output (10%): Contributes to presentations, grants, and manuscripts under supervision by mentors and peers.

　　Education QualificationsBachelor's Degree RequiredMaster's Degree biological or computational discipline Preferred

　　Experience QualificationsAt least one (1) year in applied bioinformatics, computational, and genomics/proteomics experience. Preferred

　　Skills and AbilitiesStrong UNIX/LINUX expertise required.Experience with R strongly preferred.Experience with Python, Perl, or other languages preferred.Experience with pipeline or workflow development frameworks preferred.Experience with data management preferred.Familiarity with open source and commercial bioinformatics resources and software preferred.Experience with genomic data analysis preferred.Experience or knowledge of technologies commonly used in biological labs, such as PCR, cloning, electrophoresis gels, and cell culture preferred.Knowledge