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Bioinformcatics & Biostatistics

National Center for Advancing Translational Sciences, Bethesda, MD and surrounding area

Position Description:

NCATS, a major research component of NIH, seeks applications from exceptional candidates to fill a postdoctoral bioinformatics position in the Informatics Core (IFX) within the Division of Preclinical Innovation.
 
The IFX is an interdisciplinary team of bioinformaticians, clinical informaticians, cheminformaticians and software engineers who collaborate closely with molecular biologists to augment the use of metabolomics and multi-omics analysis approaches to identify dysregulated pathways and putative therapeutic targets.
 
Core Responsibilities:
The selected candidate — a post-doctoral fellow in bioinformatics — will have a solid foundation in bioinformatics and biostatistics, including machine learning, and experience in cleaning, processing, and integrating metabolomic and other -omic datasets. He or she will develop novel bioinformatics methods to optimize the predictive capacity of metabolomics and -omic (e.g., proteomic, transcriptomic) profiles in differentiating groups (e.g., cell characteristics, individuals). These novel approaches will augment the bioinformatics field by addressing issues not addressed by standard approaches. The selected candidate will interact closely with computational and noncomputational (e.g., biologists, chemists, clinicians) IFX and NCATS scientists and our academic collaborators. In addition to working independently on collaborative translational research projects, the fellow also would be involved in building a computational infrastructure for the QC, analysis, and interpretation of metabolomic and multi-omic profiles. He or she will be expected to draft manuscripts and publish results in high-impact, peer-reviewed scientific journals and to present results at internal and external scientific meetings.
 
Qualifications:
The ideal candidate should possess a doctoral degree or equivalent in bioinformatics, biomedical informatics, or a related field and have demonstrated hands-on experience in leading the large-scale analysis of multi-omic data. Experience with metabolomics data is strongly preferred. He or she should have demonstrated experience leveraging publicly available datasets, including their organization, cleaning, and preprocessing. Applicants also should have demonstrated experience in multivariable analyses and machine/deep learning. Basic knowledge and understanding of biology and chemistry is a plus. Knowledge of R and/or Python and working within a high-performance computing/cloud environment is required.
 
The selected candidate must have excellent interpersonal, verbal, and written communication skills in English and must possess strong collaborative, organizational and recordkeeping skills; the ability to work productively as a member of a diverse and dynamic multidisciplinary team, managing multiple research studies simultaneously; and the desire to acquire new skills as required for research studies. While the team is highly collaborative in nature, the pursuit of original computational research directions by the candidate is encouraged. Applicant must be eligible to work in the United States for any employer.
 
Stipends/Benefits:
Annual stipends are provided and are based on the NIH Postdoctoral Intramural Research Training Award and Visiting Fellow scale; health insurance benefits are available. The fellow also may take part in Foundation for Advanced Education in the Sciences courses at NIH. The position is renewable for up to five years.
 

To Apply:

Please submit (via email) a cover letter describing your career goals and interest in the position, including a research summary (one to two pages), a current curriculum vitae with a complete bibliography, and the names of and contact information for at least three references to Ewy A. Mathé, Ph.D., at ewy.mathe@nih.gov(link sends e-mail).
 
The review of applications will begin immediately and will continue until the position is filled. Learn more about informatics research at NCATS.
 
 
The NIH is dedicated to building a diverse community in its training and employment programs. NIH is an Equal Opportunity Employer.