The Hoffman Lab at the Princess Margaret Cancer Centre and the University of Toronto seeks new members for our team. We develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight. A key focus of the lab is to train a new generation of computational biologists.

Postdoctoral fellowships in computational biology and machine learning 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. We also welcome your project ideas! The project should concern mammalian epigenomics. Cancer relevance preferred. 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), and the URL of a web page containing a code sample written by you (for example, on Bitbucket or GitHub) to

Graduate studentships in computational genomics and machine learning Graduate students in the Hoffman Lab must be accepted in a graduate program at the University of Toronto. Please apply to the PhD or MSc programs of either the Department of Computer Science or the Department of Medical Biophysics. Required qualifications: Admission to one of the graduate programs above. Experience in programming. Not required, but preferred qualifications: Experience in computational biology research. Coursework in computational biology. Experience in Python, R, C, and C++. Experience in Unix environments.

Undergraduate positions in computational genomics and machine learning We sometimes have computational biology projects that might work well for an undergraduate or co-op student. Please apply if interested. We participate in the Medical Biophysics Summer Student Program, the Computer Science Undergraduate Project Portal, and the Faculty of Arts and Science Research Opportunity Program. We participate in the Mitacs Globalink Research Internship for undergraduates from Australia, Brazil, China, France, India, Mexico, Saudi Arabia, Tunisia, and Vietnam. We also supervise students for programs such as the Canadian Institutes for Health Research Summer Studentship Award. University of Toronto undergraduates can get credit for independent study in your college or department. See the Faculty of Arts and Science page, "Research — Current Students". Required qualifications: Coursework in biology, computer science, electrical engineering, statistics, or physics. Experience in Python and Unix environments. Permission to work or study in Canada. Generally this means Canadian nationality, permanent residency, work permit, or study permit. Mitacs will arrange for appropriate permission if you apply through them. Not required, but preferred qualifications: Coursework in computational biology. Experience in R, C, and C++. To apply: Please submit a CV (as PDF), an academic transcript (as PDF), and indicate your expected graduation date to