The Division of Translational Medicine & Human Genetics, in collaboration with the Institute for Biomedical Informatics (IBI), is searching for a talented, experienced, and highly motivated data scientist/bioinformatician/computational biologist to perform complex biostatistical and bioinformatic analyses on a variety of ‘omic’ and tissue based assays. This position will function as part of the Fajgenbaum laboratory within the Castleman Disease Center at Penn (CDCP), both of which are working to understand the etiology of idiopathic multicentric Castleman disease (iMCD) and cell types, signaling pathways, and cytokines that drive pathogenesis in order to ultimately identify life-saving treatment approaches. iMCD is a rare and deadly immunological disorder that is extremely poorly understood. This is a unique opportunity to join a leading lab in the iMCD field; the research group is generating large-scale multi-layer ‘omics’ datasets on individual patients. Key technologies that the research team is currently leveraging or plans to leverage are next-generation DNA and RNA sequencing (WES, WGS, single cell, etc.), T and B cell repertoire profiling, flow cytometry/CyTOF, serum and tissue proteomics, and path-omics machine learning. The data scientist/bioinformatician will work directly with other members of the laboratory to analyze datasets and integrate findings to provide novel and important insights into disease drivers. A significant number of publications and presentations are anticipated, and insights will be translated into cellular assays, mouse models, and human applications.
The Fajgenbaum lab and CDCP comprises a highly motivated, patient-focused team that works closely with international collaborators and the Castleman Disease Collaborative Network. The lab recently received the first-ever R01 to study iMCD, which is funding this position. The data scientist/bioinformatician/computational biologist will be provided with support from Penn’s IBI, as well as external experts in hematology, immunology, and hematopathology.
The main responsibilities for this role will be to assist with study design and grant applications; plan, develop, implement, and maintain high-quality biomedical data analysis pipelines and bioinformatics applications; lead integration and bioinformatics analyses of data generated by investigators through application of statistical methods, machine learning, visual analytical, and other advanced applications for the analysis; present results and publish findings. This role requires performing complex computational analysis, exploration of parameter settings, comparison of results across different methods, and the summary and visualization of data and results. The candidate will also need to implement and manage biomedical data with databases, query interfaces and web applications as well as retrieve biomedical NGS data from public resources and organize the data for easy analysis and sharing.
(Description should be brief and only include principle duties.)
- Develop, implement and maintain high-quality pipelines for the processing of large quantities of next-generation sequencing (NGS) data.
- Apply statistical methods, machine learning (ML), visual analytical (VA) and other advanced applications for the analysis of (large scale) biomedical data.
- Implement and manage biomedical data with databases, query interfaces and web applications. Retrieve biomedical NGS data from public resources and organize the data for easy analysis and sharing.
- Prepare results in tabular, written summary, and graphical summary form suitable for publication and peer review.
- Provide bioinformatics support to the Fajgenbaum Laboratory and CDCP. Requires performing complex computational analysis, exploration of parameter settings, comparison of results across different methods, and the summary and visualization of data and results for presentation.
- Implements, tests, deploys, documents, and maintains analytical applications, analysis pipelines, and results reporting methodologies. This duty includes computer programming necessary to make modifications to existing algorithms and software or to write scripts to implement software in a server or high-performance computing environment.
- The minimum of a Master’s degree and three years of data analysis experience, or equivalent combination of education and experience, in Bioinformatics, Biostatistics, Computer Science, Data Science, Informatics or equivalent; PhD desirable.
- Experience with biomedical research required
- Experience with immunology desirable
- Competent in Python/Perl and R programming language required
- Experience integrating multiple large datasets to generate biological insight required
- Experience with Next Generation Sequencing data analysis desirable
- Experience with machine learning and data science a plus
- Ability to work independently and apply critical thinking and sound judgment
- Excellent organizational and time management skills
- Ability to work with a multi-disciplinary team
- Ability to perform high-level report writing and presentation skills
- Ability to communicate effectively with team members
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