We seek postdoctoral fellows for several projects in computational genomics and machine learning. Selected projects include:
- Integrating epigenomic and sequence data to better understand human gene regulation.
- Creating models of transcription factor binding that allow us to predict the effects of perturbations.
- Developing deep learning techniques to find novel behavior in multiple functional genomics datasets.
Required qualifications: Doctorate in computational biology, computer science, electrical engineering, statistics, or physics, obtained within the last five years. Submitted first-author or joint first-author papers in genomics or machine learning research. Experience in scientific programming in a Unix environment.
Not required, but preferred qualifications: Experience with epigenomics and graphical models. First-author papers published in peer-reviewed journals, refereed conference proceedings, or a preprint archive. Experience programming in Python, R, C, and C++.
Benefits: Includes extended medical insurance, dental insurance, maternity benefits (15 weeks), parental benefits (additional 35 weeks), child care program (fee applies), defined-benefit pension plan, and employment insurance. Flexible work hours.
To apply: We will accept applications until the positions are filled. Please submit your CV (as PDF), one representative paper (as PDF), the URL of a code sample, and the names, email addresses, and phone numbers of three references to firstname.lastname@example.org.