Staff Scientist in Translational Bioinformatics

Children's Hospital of Philadelphia•Philadelphia, PA

1d•$101,300 - $129,100•Hybrid

About The Position

This role is an entry level position for a PhD level professional and a 2nd stage position for those with moderate experience without a PhD. The focus of the position is service-level application of bioinformatics tools and methods to bench and clinical research problems in various biomedical domains. The position allows for a wide variety of activities described within the job responsibilities and encompasses positions within both research and clinical environments. Activities occur with a moderate degree of supervision with some latitude for independent judgment, development of bioinformatics workflows and processes, and presentation of results. This role will begin to apply best practices in collaborative science as a bioinformatics domain expert. Academic output, while not a primary focus of this position, is also expected with a moderate degree of supervision. This position is primarily focused on supporting scientific teams and projects as a bioinformatics domain expert. This role must be able to perform all responsibilities listed in the less senior roles within the career ladder. All responsibilities listed in this description are additional. Dr. Tamir Diamond, Dr. Edward Behrens and their research group at Children's Hospital of Philadelphia are seeking a highly motivated PhD-level Staff Scientist in Translational Bioinformatics to support studies of immune dysregulation in pediatric acute liver failure. The successful candidate will lead computational analyses integrating multi-omic datasets generated from patient blood and tissue samples, with a focus on translational immunology. Our group uses 10x Genomics platforms such as visiumHD, Xenium and GEM-Ex single cell RNA sequencing from blood/tissue, as well as multiprotein assays by O-Link and other vendors. Our group has a collaborative relationship with the CHOP single cell RNA sequencing core on multiple projects providing excellent resources and support.

Requirements

PhD in Bioinformatics, Computational Biology, Immunology, Genomics, or related field
Strong experience with single-cell and/or spatial ‘omics analysis
Proficiency in R and/or Python
Experience working with high-dimensional human translational datasets
Excellent communication and collaborative skills
At least three (3) years of applied bioinformatics, computational and/or genomics/proteomics experience
Intermediate proficiency in UNIX/LINUX
Intermediate proficiency in programing languages (Python/Django, R, Perl, Scala, Ruby)
Intermediate proficiency in pipeline or workflow development frameworks
Intermediate proficiency in biostatistical data analysis on dimensional data, genomics and research data
Intermediate proficiency in data management
Intermediate proficiency in genomic data sets and analysis tools (UCSC Genome Browser, Bioconductor, ENCODE, NCBI databases)
Intermediate proficiency in open source and commercial bioinformatics resources and software
Intermediate proficiency in source code management, application development, and project lifecycle management
Intermediate proficiency in bioinformatics analysis, statistical modeling, data integration, and bioinformatics best practices
Substantial knowledge of relational database management systems (PostgreSQL, MySQL, Oracle)
Substantial knowledge of bioinformatics applications and algorithms
Substantial knowledge of biological domains
Substantial knowledge of technologies commonly used in biological labs (PCR, cloning, electrophoresis gels, and cell cultures)
Substantial knowledge of working mechanism of microarray, NGS, mass spectrometry, or other high-throughput technologies
Excellent verbal and written communications skills
Strong time management skills
Strong organizational skills
Strong presentation skills
Strong critical thinking / problem-solving skills
Strong project management skills
Ability to maintain confidentiality and professionalism
Ability to work independently with minimal supervision
Ability to gather, analyze and make recommendations/decisions based on data / best practices
Ability to convey complex or technical information in an easy-to-understand manner
Ability to collaborate with stakeholders at all levels
Must be willing to commit to the position for at least 2 years.

Nice To Haves

Experience with immune repertoire analysis (TCR/BCR sequencing)
Familiarity with translational immunology and human tissue datasets
Experience with integrative multi-modal analysis approaches
Master's Degree in bio/informatics, computational biology, computer/information science, biomedical engineering, biological science or a related field
At least five (5) years of applied bioinformatics, computational and/or genomics/proteomics experience

Responsibilities

Analyze and integrate datasets from: Single-cell RNA sequencing TCR/BCR repertoire sequencing Spatial transcriptomics Multiplex immunofluorescence/imaging platforms Multiplex protein assays
Perform cell-state, clonality, pathway, and cell-cell interaction analyses
Develop reproducible computational workflows in R/Python within HPC environments
Contribute to manuscripts, abstracts, and grant applications
Contribute to the development of application portfolio by developing knowledge of internally developed systems, open-source programs, and commercial applications.
Provide efficient data management support.
Use standard pipelines for data processing and manipulation in advance of performing analysis in a manner that best enables the analysis plan.
Contribute to the development of additional pipeline functionality and changes by providing knowledge of both collaboration-specific requirements and bioinformatics discipline advances.
Advocate for specific collaboration requirements for continual advancement of shared pipeline and code resources.
Provide collaboration-specific transparency for data processing and pre-analysis, including sample- and cohort-level status.
Code and generally support code and applications on behalf of collaborative project and/or team.
Within the context of the collaboration or project, develop and apply best practices to code development.
Establish requirements with the project team.
Review existing applications and code sources (both commercial and open source) and selection of best strategy for development or adoption.
Advocate for chosen strategy to project team by showing value of approach
Develop best practices for project-based code development, QC, and execution consist with the expectations of specific collaborations.
Regularly seek peer-to-peer code reviews by participating in informal and formal critical code reviews.
Analyze data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data primarily under the direction of the collaborative project team.
Develop robust analysis plans independently with regular peer-to-peer review in both informal and formal settings.
Incorporate more advanced applications and methods into analysis.
Develop at least one specialty analytical or biomedical area that serves the collaborative team.
Establish role within collaborative project team as primary bioinformatics resource.
Contribute to and influence project-level management by serving as bioinformatics point.
Define and promote boundaries of support by assessing all stakeholders, including bioinformatics management, collaborator expectations, and funding levels and mechanisms.
Regularly discuss satisfaction and expectations with collaborators; continually advocate for clear understanding of role.
Develop new collaborations with high degree of supervision.
Develop presentations, grant sections, and manuscript sections with subsequent review by peers and mentors.
Regularly contribute to bioinformatics-focused manuscripts and publications.
Regularly contribute to podium presentations and posters.
Contribute to bioinformatics sections of grant and award proposals.