Ferring Pharmaceuticals is a globally recognized, research-driven, biopharmaceutical company with more than 65 years of history. Headquartered in Switzerland, Ferring is privately owned with over 5,700 employees in nearly 60 countries. In the United States, Ferring identifies, develops and markets innovative products in the fields of reproductive health (infertility), urology, gastroenterology, endocrinology, women’s health (obstetrics/gynecology) and orthopaedics. Ferring’s US operations employ approximately 800 people.
The Ferring Research Institute was established in San Diego, California in 1996 as the company’s center of excellence for peptide research. More than 70 people work at its state-of-the-art research facility located in the heart of the Southern California biopharmaceutical community.
Computational post-doc in FRI’s Translational Research group will engage in external collaborations with leading academic researchers in the reproductive and women’s health space and potentially other areas of strategic interest. Collaboration opportunities include microbiome community and functional profiling, RNAseq and other –omics data analysis and integration. The Post-Doc candidate will also work with FRI scientists to translate results into early stage preclinical drug discovery projects.
- Perform microbial community analysis of human microbiomes from longitudinal profiling and intervention studies relating to reproductive health. Identify differences in community structures and dynamics, and generate testable hypotheses for follow-up.
- Analyze longitudinal human RNAseq data from disease models and human study participants. Integrate transcriptomics data with other data modalities (eg. inflammatory markers, metabolomics data, proteomics), and generate hypotheses on disease mechanisms and follow up experiments
- Design and analyze genomics experiments to characterize preclinical models of human diseases. Perform cross-species expression- and pathway analyses, and assess translatability from models to human disease
- Collaborate with internal scientists at FRI to translate therapeutic and biomarker hypotheses resulting from academic collaborations into industry-relevant preclinical research projects.
- Lead and contribute to publications resulting from above collaborations, as well as any methodological innovations, eg. new methods, improved data interpretation and integration
- Ph.D. in biostatistics, genomics, bioinformatics, computer science or related field
- Expertise in biostatistics, computational biology and genomics strongly preferred
- Experience in analysis and interpretation of NGS data and integration with other sources
- Expertise in microbiome analysis preferred but not required
- Excellent communication and programming skills
- Demonstrated applied bioinformatics proficiency as evidenced by relevant publications in peer-reviewed journals.