The Bioinformatics Scientist I position is an entry level position for a non-PhD level professional. The focus of the position is tailored analysis of genetic data and other complex molecular data types collaboratively support researchers at CHOP. In addition the candidate will provide domain expertise and help guide the software engineering team to develop enterprise bioinformatics applications. Finally, they will support internal bioinformatics initiatives, 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 also rely on a level of peer-to-peer mentorship. The Bioinformatics Scientist I is primarily focused on the support of higher level bioinformatics personnel but will have direct interaction with collaborators and investigators to work on translational and research projects.
Data Analysis (60%): Analyzes data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data under supervision of mentors and peers. • Works with bioinformatics group members and research investigators to analyze whole exome and whole genome sequencing data. • Stays current with evolving algorithms and methods of WES and WGS analysis. • Stays current with biological databases, tools, and resources to help annotate and prioritize variants and genetic lesions.
• Integrative analysis of multiple data types, genomic, phenotype, annotation etc… • Statistical analysis and machine learning on data to support hypothesis-driven or data-driven research. • Gathering, summarizing, and visualization of genomic or other types of biological data. • Strong knowledge of biological entities and concepts to accelerate the research process. • Maintains working knowledge of available commercial and openly accessible knowledge bases as they apply to bioinformatics analysis.
Coding (20%): 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. • Continually keeps abreast of evolving data generation platform fundamentals, file-specific information representation, and strategic application of code base to optimize value of data. • 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.
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. • Provides bioinformatics domain expertise and potentially prototypes to software engineering team. • Establishes relationships with researchers and groups to provide continued support on disease or domain specific initiatives.
Academic Output (10%): Contributes to presentations, grants, and manuscripts under supervision of mentors and peers.
Required Education and Experience
Required Education: Bachelors or Masters in biological or computational discipline.
Required Experience: 0-4 years in applied bioinformatics, computational, and genomics/proteomics areas. Preferred Education, Experience & Cert/Lic
Additional Technical Requirements
• Strong 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 databases / SQL. • Familiarity with open source and commercial bioinformatics resources and software preferred. • Experience with genomic data analysis preferred. • Knowledge of technologies commonly used in biological labs, such as PCR, cloning, electrophoresis gels, and cell culture preferred. • Knowledge of the working mechanism of microarray, NGS, mass spectrometry, or other high-throughput technologies and awareness of their strengths and weaknesses, as well as applicability to a specific biological problem is preferred. • Familiarity with resources of genomic data sets and analysis tools, such as UCSC Genome Browser, Bioconductor, ENCODE, and NCBI databases is preferred. • Accountability and attention to timelines. • Excellent organization and communication skills with an emphasis on strong presentation skills. • Ability to work in a team environment.
Please apply through: https://careers.chop.edu/job/Philadelphia-Bioinformatics-Scientist-I-PA-19104/410522100/