-
Purdue’s strategic focus on health equity and population health. Program Goals and Learning Objectives The fellow will gain experience in: Designing and conducting pharmacoepidemiologic studies in cancer and
-
and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
-
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
-
discussions for other timelines are possible. Qualifications: PhD in a broadly related field (e.g., cognitive science, computer science, psychology, learning sciences, linguistics, speech-language-hearing
-
Requirements REQUIRED: PhD in molecular biology, cell biology, genomics, biophysics, or any closely related field. Experience in chromatin is desired not required. The candidate is expected to have excellent