Genetics Research Biologist

Computational Biologist

We deliver strategic workforce solutions that help you manage your talent and business more efficiently and effectively. Since launching in 1996, IRI has attracted, assembled and retained key employees who are experts in their fields. This has helped us expand into new sectors and steadily grow.

We've stayed true to our focus of finding qualified and experienced professionals in our specialty areas. By continually exceeding their expectations, we have built successful ongoing partnerships that help us stay true to our commitments of performance and integrity.

We forge partnerships that are meant for the long term and align skills and cultures. Our client is a multinational biotechnology company, headquartered in the US, whose goal is to ensure that people everywhere have access to innovative treatments and quality health care. Through working in partnership with everyone from patients to health care providers and managed care organizations to world governments and non-governmental organizations, they ensure to continue to deliver on their commitments to the patients, customers, and shareholders who rely on them.

The Epigenetics Group is seeking a scientist who is passionate about leveraging computational biology to create life-changing therapies for patients with degenerative diseases

• The scientist will work within Epigenetics and collaboratively with other discoveries, translational and clinical scientists to design experiments that probe multiple 'omic dimensions (e.g., transcriptome, proteome, genome, epigenome), to use creative analytical approaches to reveal drug targets and biomarkers, and to generate insights into mechanisms of action
• The Scientist will become expert in the interrogation of bench- and patient-derived high-throughput data sets to produce new insights into fundamental biology and to further the development of effective therapies

Experience and strong proficiency in the analysis and integration of multiple 'omics data sets

• Familiarity with high-throughput platforms for analysis of: coding and non-coding transcriptomes; Knowledge of modern object-oriented and statistical programming techniques, and languages (e.g., R, Python, MATLAB, Java, C/C++)
• Knowledge of current NGS analysis algorithms and toolsets (e.g., STAR, Trinity, Tuxedo, HOMER, MACS, GATK, Galaxy), and comfort using local and cloud-based UNIX compute environments
• A strong background in statistics and/or machine learning, and knowledge of modern pathway discovery and network analysis techniques
• S. plus three years' experience in life science research, with a degree in cell biology, molecular genetics or a related discipline (background flexible). Candidates with PhD's may also be considered