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Center for Data-Driven Discovery in Biomedicine (D3b -, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania

Position Description:

The Bioinformatics Team within the Center for Data-Driven Discovery in Biomedicine (D3b - at the Children’s Hospital of Philadelphia (CHOP) is seeking a talented postdoctoral fellow to carry out a mentored, bioinformatics (computational) research project within the field of oncology, focused on discovery of novel oncogenic mechanisms of pediatric brain tumors. The postdoc experience will serve to extend, refine, and enhance skills necessary for professional and career development, and will enable the individual to broaden his/her scientific background by acquiring new research capabilities. 


It is expected that this individual will conduct independent scholarly research, and will contribute directly to the overall research goals of the project and the research group. Postdocs will be expected to participate in project planning, recording, and interpretation/evaluation of data, and communication of results. Postdocs will also be expected to acquire technical, lab management, and manuscript/grant writing skills; and participate in seminars, lectures, poster sessions and presentations at national meetings. Postdoctoral fellows also may be required to supervise junior team members, develop new bioinformatics methods for research, and assist with the development of other research projects in the center. Responsibilities include:

Pre-Analysis (20%) - 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.

Coding (20%) - 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.

Data Analysis (20%) - 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.

Collaboration (20%) - 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.

Academic Output (20%) - Develop presentations, grant sections, and manuscript sections with subsequent review by peers and mentors:

  • Present research findings at relevant conferences;
  • Lead bioinformatics-focused manuscripts and publications;
  • Contribute to bioinformatics sections of grant and award proposals.


This candidate will have a terminal degree PhD, MD, DVM, etc. and will assume responsibility for a specific, on-going research project under the direction/guidance of Dr. Jo Lynne Rokita (within the D3b center led by Drs. Adam Resnick and Jay Storm). The postdoctoral fellow will generate hypotheses and utilize and integrate WGS, RNA-Seq, and potentially extend analyses to include miRNA-Seq, methylation arrays, single-cell RNA-Seq, proteomics, and/or drug screen data. Current research projects in the group include characterization of pediatric brain tumors with alternative lengthening of telomeres (ALT), gene fusion annotation and prioritization, and genomic characterization of brain tumor models.


  • Ph.D., M.D., or D.V.M. in biological or computational discipline;
  • Experience in applied bioinformatics, genomics, and computational work;
  • Experience with management and analysis of complex data types;
  • Experience with genomic and/or proteomic data analysis methods;
  • Doctorate Degree in biological or computational discipline (preferred);
  • Four (4) years of research experience in applied bioinformatics, genomics, and computational work. This experience can be inclusive of a relevant PhD dissertation (preferred);
  • Fluency in two or more of: R, Python, Perl, bash, high-performance cluster computing, and/or cloud computing (preferred);
  • Experience with pipeline or workflow development frameworks (preferred);
  • Experience or knowledge of array/sequencing technologies commonly used in biological labs, such as RNA-Seq, WGS, WES, miRNA-Seq, SNP arrays, single cell sequencing, proteomics (preferred).

To Apply:

Interested candidates should contact Jo Lynne Rokita, PhD, Supervisory Bioinformatics Scientist, at