Our group exists to train people to study statistical, population and evolutionary genetics using quantitative approaches. Lab members may come from a variety of backgrounds. As part of their work, lab members analyze (typically big) genomic data, develop mathematical/statistical models and/or computational analysis tools. Members of the lab have extensive latitude to design their own projects within our broad areas of interest.
The group has lab spaces in both the Health Discovery Building (HDB), part of the Dell Medical School and at the Patterson Labs (PAT) building, part of the College of Natural Sciences.
We are looking to recruit curious and motivated scientists at all levels and informal inquires are welcome. Candidates from diverse scientific and personal backgrounds are especially encouraged to apply.
We are looking to hire postdocs. Prospective postdocs must have a quantitative background, programming skills and/or extensive experience with genomic data analysis, as well as a sincere interest in tackling biological questions. Positions in the lab offer a competitive salary and benefits. Informal inquiries as well as applications (including a cv, a cover letter that briefly describes your research experience, interests and goals for your postdoctoral training, examples of your work and contact details for 2-3 professional references) should be sent over email.
We are looking to recruit graduate students with an interest in evolution and genetics, and preferably a strong quantitative background. Options for doctoral programs include the Ecology, Evolution and Behavior program and the Cell and Molecular Biology (research tracks: Bioinformatics and Computational Biology or Molecular Genetics).
It is a good idea to contact us in advance if you are considering applying to one of these graduate programs and interested in joining us. I will do my best to help you with the admission process.
Undergraduates, Master’s students, and others
People interested in joining the lab should write to Arbel with a CV, relevant course history, grade transcript and statement of interest. Undergraduate and Master's student must have a strong quantitative and/or computational background. Undergraduate research effort in the lab is compensated either in academic credit or hourly pay. In cases of a compelling research fit, students at other institutions may be able to arrange for paid summer or remote internships.