We aim to generate computational approaches for interrogating large-scale multi-omics datasets and patient transcriptome data, thereby combining evidence across molecular layers to dissect genetic and non-genetic risk factors for neurological diseases.
The successful applicant will hold a doctoral degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical work.
Previous experience in developing and applying computational methods applied to large datasets is expected. Expertise in analysis and integration of multiomics data, statistical genetics, statistical interpretation and analysis of next-generation sequencing datasets is beneficial.
Applicants should send their curriculum vitae, a cover letter detailing their interest in the lab’s research, and names and addresses of three references.