The AshleyLab seeks a highly motivated and skilled postdoctoral researcher to lead multifaceted machine learning projects harnessing large-scale genomic, transcriptomic, proteomic, and imaging and clinical data. The researcher will have access to data from a unique combination of clinical trial registers (academic and industry), biobanks and real-world EHR data.
Project themes will span enhanced risk prediction, clinical trial patient selection and optimization, and the use of omic data to reveal molecular etiology for therapeutic targets. The researcher will utilize clinical biostatistical analysis, genome wide association analysis, and machine learning approaches including deep learning-based frameworks.
The researcher will have the opportunity to work in a highly collaborative environment committed to team science that will include other collaborating scientists (wet and dry), physicians, postdocs, technicians, and students.
- Cover letter including statement of interest, research experience, and career goals (2 pages max)
- Curriculum vitae
- Contact information for 3 references
