Postgraduate Associate Genetics, Reilly Lab
The Reilly Lab in the Department of Genetics at Yale School of Medicine (www.reilly-lab.com) is seeking postgraduate researchers in computational biology. We’re a collaborative, hard-working, and supportive team that develops and use cutting-edge genomic tools to study human disease and evolution.
The promise of unlocking the human genome’s full potential to cure disease or understand our evolutionary history hinges on our ability to build new tools for interpreting uncharacterized genomic regions. To that end we’ve developed CRISPR editing, high-throughput reporter assays, and machine learning methods. Our lab applies these tools to understand evolutionarily significant genomic loci, the precise genetic mechanisms underlying complex traits, and disease risk for neurological, autoimmune and metabolic disorders. We are looking for strong candidates with either a human and cross-species evolutionary genomics focus, or an interest in technology development in the human genetics space.
TRAINING
The Postgraduate Associate will train in developing new computational tools and techniques to advance our understanding of the human genome and its role in disease and evolution. Potential projects include applying machine learning models and population genetic methods to predict and understand regulatory variants, collaborating with experimental biologists on developing novel uses of high-throughput reporter assays, and analyzing CRISPR editing and high-throughput reporter assay data to uncover new insights into the genetics of human disease and evolution. The Postgraduate Associate is expected to develop into an integral, valued member of the lab, to participate in weekly lab meetings/journal clubs, to present their research findings, and to attend research seminars. There is some flexibility to match the trainee’s interests and aptitude to specific computational projects of interest.
MENTORING
The Reilly lab takes seriously its role in training future scientists and sees the postgraduate’s future success as the lab’s success. The Postgraduate Associate will meet regularly with the PI to discuss scientific progress and career development. Previous trainees have gone onto top-tier graduate programs, medical schools, and industry positions. Each has graduated from the lab with authorship on at least one manuscript. As a part of the Department of Genetics at the Yale School of Medicine, the lab offers an outstanding and fully resourced training environment which provides the flexibility to meet the trainee’s professional goals.
EDUCATION
For computational candidates, excellent coding skills and coursework in molecular biology/genetics are required. The candidate should display a high level of initiative, logic, and creative problem solving skills, as well as a bachelor’s degree with a solid foundation in science. The candidate is also required to have excellent personal initiative and should be excited by the prospect of working in a dynamic team. They should demonstrate previous time management skills in coordinating multiple, concurrent assignments in a multi-faceted project. Candidates should possess strong communication and computer skills, with the ability to develop technical documents and presentations.
Qualifications
Candidates with any experience in machine learning, bioinformatics, sequencing, molecular biology, genetics, or evolutionary biology are especially encouraged to apply. The appointment will be for 1 year, with the possibility of extension or further opportunities
Application Instructions
Interested candidates should apply via Interfolio. The application should include: (1) CV; (2) a cover letter including a brief description of research interests and how they align with the lab; and (3) contact information for 2-3 referees.
Equal Employment Opportunity Statement
Yale University is an Affirmative Action/Equal Opportunity employer. Yale values diversity among its students, staff, and faculty and strongly welcomes applications from women, persons with disabilities, protected veterans, and underrepresented minorities.