Monday, June 13, 2022 to Friday, June 17, 2022
The University of Virginia is organizing a Biomedical Data Science Innovation Lab to foster the development of new interdisciplinary teams via a facilitated and mentored format to tackle data science challenges arising in the ethical use of biomedical artificial intelligence (AI). A more detailed description of the Lab can be found in the document Detailed Information on 2021-2022 Biomedical Data Science Innovation Lab.
Involving around 30 competitively-selected, early-career (post-doc, assistant to early associate professor level) biomedical and data science investigators, each year’s Biomedical Data Science Innovation Lab strives to develop new and bold approaches to address challenging biomedical questions for topics that could benefit from a fresh or divergent quantitative perspective. The Biomedical Data Science Innovation Lab involves an academic year-long series of stimulating online “microlab” activities aimed at examining the scale and scope of the targeted biomedical research domain, reviewing potential data science solutions, and for sparking creative thinking. Guest lectures throughout provide context, insight, and challenge participants to think deeply about how data can drive new thinking about biomedical problems. Prior topics have included mobile health, single cell dynamics, the microbiome, rural health and environmental exposures, and in 2021, the brain. Activities culminate in an intensive five-day residential workshop facilitating interdisciplinary teams toward the generation of multidisciplinary research programs. Peer and mentored feedback serve to provide critical input on projects, rigor, and polish. Prior knowledge of research at the interface of the biomedical and data science is not required; rather, candidates with either quantitative (i.e. AI, data science, mathematics, etc.) or biomedical (i.e. ethics, medical informatics, population-science, etc.) expertise who demonstrate their willingness to engage in collaborative multidisciplinary research are highly encouraged to apply. Women scientists and researchers from under-represented minorities are particularly welcome. Exemplar areas of quantitative interest are suggested in the document Quantitative Topics of Expertise Needed and biomedical interest are suggested in the document Biomedical Topics of Expertise Needed.