-
Sequencing (GBS), Whole Genome Sequencing (WGS) and targeted genotyping chips (e.g. MassArray) and analyze them together with environmental data using population genetics and machine learning tools
-
interdisciplinary projects explore how patterns in baby teeth reflect past environmental exposures and predict future mental health outcomes. The research integrates biological measures with developmental and
-
engage fully in the lab’s dynamic environment. Required: Ph.D. in a relevant field such as Biology, Biochemistry, Epidemiology, Genetics, Genomics, or Psychology Strong publication record, including first
-
the following areas: Performing and/or analyzing functional genomics experiments Competence with Unix environment, R, Python, high performing cluster Familiarity with machine learning Have taken coursework in
-
implementation, virtual reality visualization, and more. Core Competencies Applicants must demonstrate strong writing and communication skills, the ability to function in a team environment with other researchers
-
coding environments (e.g., R, Python). Ability to work collaboratively with a team of diverse backgrounds. Excellent written and verbal communication skills. Experience in processing large data sets