TENURE-TRACK INVESTIGATOR IN SINGLE-CELL GENOMICS

Updated: 11 days ago
Location: Bethesda, MARYLAND
Deadline: 30 Jul 2024

TENURE-TRACK INVESTIGATOR IN SINGLE-CELL GENOMICS
National Library of Medicine, Bethesda, Maryland

The National Library of Medicine (NLM), a component of the National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS), is recruiting for a tenure-track investigator within its Intramural Research Program (IRP) in Bethesda, MD. The recruitment is part of a planned expansion of NLM’s intramural research in computational health sciences. The goal of this search is to identify candidates with the potential to advance the processing, analysis, and interpretation of single-cell genomics data. The successful candidate will contribute to groundbreaking research in the following key areas of Single-Cell RNA Sequencing-Based Cellular Phenotyping, Spatial Transcriptomics Analysis, Single-Cell Epigenomics Analysis, and Semantic Knowledge Graph Representation.

Recent advances in sequencing technology are enabling the capture of genomic and transcriptomic sequence data at the single cell level. This technological revolution in the laboratory has resulted in the need to develop and apply novel computational methods for processing and analyzing these data that are both statistically rigorous and scalable to the volume of data being generated. In addition, semantic representation of the knowledge derived from the processing, analysis, and interpretation of these data is needed in order to maximize the impact of these studies.

The recruitment is part of a planned expansion of NLM’s intramural research in computational biology and data sciences. NLM has identified as a strategic research priority the development of innovative computational and statistical techniques applied to the analysis and interpretation of single cell genomics data and its translation into computable knowledge in support of diagnostic biomarker and therapeutic target discovery.

The scientist will concentrate on pioneering computational and statistical techniques, specifically designed for analyzing and interpreting single-cell genomics data. This expertise will play a crucial role in translating data into computable knowledge, supporting the discovery of diagnostic biomarkers and therapeutic targets.

We are looking for individuals with demonstrated expertise in computational, statistical, and artificial intelligence methods, proven track record of impactful research in single-cell genomics, as evidenced by publications and contributions to the field, and ability to work collaboratively in an interdisciplinary research environment.
The ideal applicant has a strong background in non-parametric statistical testing and extensive experience working with and analyzing single cell transcriptomics data as demonstrated through publications in leading journals and conferences. We are seeking individuals who are recognized national or international experts; who apply creative solutions to complex big data problems; have original scholarly scientific contributions of major significance; and who has skills in applying innovative AI approaches to complex biomedical research problems. The incumbent will exercise scientific judgment and have a data science perspective as it relates to biomedical informatics to design, develop, and implement biomedical research plans that meet the standards of the IRP at the NIH. This specialized interdisciplinary position requires combined expertise in a variety of fields including biostatistics, machine learning, and transcriptomics data analysis.

The successful candidate with high-quality interpersonal skills will join a diverse, collegial, and cooperative group of investigators within NLM that provides the opportunity for high-quality
mentoring. The selected candidate will be supported with long-term, stable resources equivalent to those provided to tenure-track faculty in an academic department, including positions for post-doctoral fellows and a budget for software, consumables, and equipment. NLM will provide excellent computational facilities and support for the rapid achievement of research goals. The broader NIH campus and NLM’s IRP provide a rich and highly interactive computational biology and biomedical informatics environment.

Applicants must have a doctorate degree or its equivalent in a pertinent field with extensive postdoctoral experience, as well as a strong publication record demonstrating potential for creative research.

Salary and benefits are competitive, commensurate with education and experience. This position is subject to a background investigation.

Prospective candidates are encouraged to submit the required materials listed below, ensuring that the announcement number NLM8509-2024 is included in their cover letter. Kindly forward the documents electronically to [email protected].
• Cover Letter
• Curriculum Vitae, including a description of mentoring and outreach activities in which you have been involved, especially those involving women and persons from other groups that are underrepresented in biomedical research
• A statement no longer than three pages of research interests, goals, and experience
• Copies of three publications or preprints
• Names of three references with their contact information

We will begin evaluating applications on May 17, 2024. Applications will be accepted until the position is filled.

Appointees may be U.S. citizens, resident aliens, or non-resident aliens with, or eligible to obtain, a valid employment-authorization visa.

Applications from women, minorities and persons with disabilities are strongly encouraged. Selection for this position will be based solely on merit. NIH does not discriminate on the basis of race, color, religion, sex, national origin, politics, marital status, sexual orientation, physical or mental disability, age or membership or non-membership in an employee organization. Along with the NIH, the NLM is dedicated to building a diverse intellectual community in its professional scientific and training programs.

DHHS and NIH are Equal Opportunity Employers



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