Location: Philadelphia, PA
Cap-Exempt H-1B Position — No lottery required
The Wistar Institute has an opening for a Bioinformatics Analyst in the laboratory of Dr. Noam Auslander. We are seeking a highly skilled candidates to bring deep expertise in computational biology and biostatistics, with a strong track record of applying analytical approaches to complex biological data, particularly in cancer and microbiome research. Key Responsibilities - Design, develop, and implement computational pipelines for the analysis of high-throughput genomic and microbiome datasets - Perform advanced statistical analyses and modeling of large-scale biological data - Develop and maintain reproducible workflows using Python, R, and Linux-based environments - Conduct data processing, integration, and quality control across diverse data types (e.g., sequencing, metagenomics) - Create clear and compelling data visualizations to communicate findings to both technical and non-technical audiences - Contribute to software/package development and documentation for internal and external use - Collaborate closely with cross-functional teams including biologists, clinicians, and data scientists - Lead or contribute to manuscript preparation, figure generation, and publication efforts Qualifications - PhD in Biostatistics, Computational Biology, Bioinformatics, or a related field - 10+ years of experience working in Linux/Unix environments - Strong programming skills in Python and R - Proven experience in data visualization, statistical analysis, and large-scale data processing - Demonstrated experience in building and maintaining bioinformatics tools or packages - Strong publication record, with experience in scientific writing and manuscript preparation - Domain expertise in cancer biology, microbiome research, and/or computational genomics Preferred Skills - Experience with cloud computing or high-performance computing environments - Familiarity with workflow management systems (e.g., Snakemake, Nextflow) - Knowledge of machine learning approaches applied to biolo