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| 【有奖交流】积极回复本帖子，参与交流，就有机会分得作者 loriy 的 13 个金币 ，回帖就立即获得 1 个金币，每人有 1 次机会 | |||
[交流]
美国NIH NCAT招聘信息学相关专业博后二名
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Sample TextPostdoctoral Fellow in Clinical and Biomedical Informatics, Division of Preclinical Innovation, Informatics Core at NCATS/NIH National Institutes of Health National Center for Advancing Translational Sciences Division of Preclinical Innovation Informatics Core Rockville, Maryland Description NCATS, a major research component of NIH, seeks applications from qualified candidates to fill a postdoctoral fellowship position in the Informatics Core within the Center’s Division of Preclinical Innovation. Applicants to this intramural program should have a background in clinical informatics with an interest in data science. The Informatics Core is a dynamic, interdisciplinary team of clinical, bio- and chem-informaticians, translational researchers, and project managers interested in evaluating drug–disease relationships. For these assessments, the team uses knowledge sources containing clinical, -omic and in vitro assay data (e.g., high-throughput screening) that are curated and/or supported and managed at NCATS. Relevant knowledge sources include but are not limited to the Genetic and Rare Diseases Information Center (GARD), Pharos and Inxight(link is external). The goal is to bridge preclinical and clinical assessments to find new putative targets. Candidates with a solid understanding in database management, integration of multiple data sources, data cleaning/processing/harmonization, interoperability and machine learning are preferred. Experience with various types of data sets as listed above is preferred. Although the team is highly collaborative in nature, the candidate’s pursuit of original research directions is strongly encouraged. Core Responsibilities The successful candidate will collect, analyze and curate data from clinical trials, U.S. Food and Drug Administration (FDA) drug labels and FDA orphan designations to elucidate the therapeutic development landscape of diseases, including rare diseases. He or she will identify relevant associations of clinical and molecular factors (e.g., genetic, -omics, etc.) and disease, including rare outcomes and response to treatments. Patient data will be accessed through various electronic health records systems, resources and programs available at NIH (e.g., Biomedical Translational Research Information System, NIH Clinical Center, Clinical and Translational Science Awards [CTSA] Program Data to Health Coordination Center [CD2H], National COVID Cohort Collaborative [N3C] and the Biomedical Data Translator program). The successful candidate then will develop new and robust code to automate the use — and augment data resources — of existing knowledge warehouses, including those developed within NCATS, and contribute to efforts for standardizing and developing new ontologies (e.g., GARD ontology, etc.). He or she is expected to use state-of-the-art linear and nonlinear multivariable modeling and machine learning to identify aforementioned relevant associations and to support clinical decision-making. The candidate will work closely with bioinformaticians, scientists and clinicians to interpret findings and identify areas that require further investigation (e.g., screening or molecular profiling). He or she will present results to the team and to the wider scientific community, draft manuscripts and publish results in peer-reviewed journals, and develop and implement novel approaches when standard approaches are not sufficient. Qualifications The ideal candidate should possess a doctoral degree or equivalent in clinical informatics, biomedical informatics, bioinformatics, or a related field and have demonstrated hands-on experience in leading the analysis of a large (multiple hundreds or greater) cohort data set. He or she should have demonstrated experience in organizing, cleaning and harmonizing large data sets, as well as in applying robust statistical methods, including multivariable analyses, machine learning, etc. Knowledge of R and/or Python is required, and basic knowledge and understanding of clinical and biological interpretation of molecular data (e.g., -omics, assay screening data, etc.) is preferred. The selected candidate should have excellent interpersonal, verbal and written communication skills in English and should 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. Applicants should be eligible to work in the United States for any employer. Stipends Annual stipends are provided and are based on the NIH Postdoctoral Intramural Research Training Award and Visiting Fellow scale. The position is renewable for up to five years. How 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 Qian Zhu, Ph.D. at qian.zhu@nih.gov. The review of applications will begin immediately and will continue until the position is filled. Learn more about intramural research at NCATS. |
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tzynew2楼
2022-03-27 10:42
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loriy(金币+1): 谢谢参与
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2022-03-27 11:50
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loriy(金币+1): 谢谢参与
2022-03-28 11:53
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loriy(金币+1): 谢谢参与
nono20097楼
2022-03-31 11:00
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loriy(金币+1): 谢谢参与
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2022-07-18 17:36
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科研王工9楼
2022-09-25 09:01
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loriy(金币+1): 谢谢参与
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2022-09-25 17:36
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