The Fisk-Meharry-Vanderbilt Biomedical Informatics Ecosystem to Support Diverse Students in Data Science
Fisk-Meharry-Vanderbilt 生物医学信息学生态系统支持数据科学领域的多元化学生
基本信息
- 批准号:10631467
- 负责人:
- 金额:$ 13.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-15 至 2027-08-31
- 项目状态:未结题
- 来源:
- 关键词:Academic Medical CentersApplied ResearchAwardCareer ChoiceCollaborationsComputational ScienceDataData ScienceDevelopmentEcosystemEducationEducational ActivitiesEducational CurriculumEnsureFacultyFoundationsFutureGrantHistorically Black Colleges and UniversitiesInstitutionInstructionJointsMentorsMethodologyMethodsProcessProgram EvaluationResearchResearch Project GrantsSchoolsSeriesStudent recruitmentStudentsSupervisionTalentsTrustUnderrepresented PopulationsUniversitiesbasebiomedical data sciencebiomedical informaticscareercomputer sciencediversity and equityexperiencefaculty researchgraduate studentmedical schoolsnoveloutreachprogramsresearch and developmentresponsible research conductskill acquisitionsummer programsummer researchtooltraining opportunityundergraduate student
项目摘要
Project Summary (Abstract)
Fisk University, Meharry Medical College, and Vanderbilt University Medical Center (VUMC)
propose a novel collaborative program to engage diverse undergraduate and graduate students
in meaningful biomedical informatics and biomedical data science summer research
experiences. The Biomedical Informatics Ecosystem to Support Talented Diverse Students in
Data Science (BEST-DS2) program builds on a strong foundation of collaboration among three
postsecondary institutions in Nashville and connects three strong data science programs: Fisk’s
computer and data science program, Meharry’s School of Applied Computational Sciences, and
Vanderbilt’s Biomedical Informatics program. The BEST-DS2 specific aims are to: (1) establish
meaningful high-quality short-term research experiences for talented diverse students; (2)
prepare these students for future educational and career opportunities in biomedical informatics
and biomedical data science; (3) provide a rigorous evaluation of the program; and (4) build a
regional and sustainable ecosystem in biomedical informatics and biomedical data
science. Both Fisk and Meharry are Historically Black Colleges and Universities (HBCUs) with a
high proportion of students from groups under-represented in biomedical informatics and
biomedical data science; VUMC provides substantial expertise in successful summer research
experiences through the Vanderbilt Biomedical Informatics Summer Program. Each summer,
three undergraduate students from Fisk and three graduate students from Meharry will join the
12-week BEST-DS2 program, for a total of 30 students over the five years of the award. At the
beginning of the summer program, a two-week bootcamp led by Fisk, Meharry, and VUMC
faculty will cover common methods and tools used in biomedical informatics and biomedical
data science. Students will receive instruction on Responsible Conduct of Research (RCR) and
engage in professional development activities (including some based upon the Entering
Research curriculum from the Center for Improvement of Mentored Experiences in Research).
Students will also participate in a Biomedical Informatics Summer Seminar Series to explore
cutting-edge topics, career pathways, and training opportunities. This five-year program will also
reach an additional 50 students from HBCUs as part of online BEST-DS2 outreach activities. In
addition to preparing diverse students for their future in biomedical informatics and biomedical
data science, the BEST-DS2 program will enable Fisk, Meharry, and VUMC to develop a
sustainable biomedical informatics and biomedical data science ecosystem, which will support
educational and research collaboration among trainees and faculty at the three institutions.
项目摘要(摘要)
项目成果
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{{ truncateString('Fortune Mhlanga', 18)}}的其他基金
The Fisk-Meharry-Vanderbilt Biomedical Informatics Ecosystem to Support Diverse Students in Data Science
Fisk-Meharry-Vanderbilt 生物医学信息学生态系统支持数据科学领域的多元化学生
- 批准号:
10705269 - 财政年份:2022
- 资助金额:
$ 13.9万 - 项目类别:
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