The Broad Institute of MIT & Harvard, a world leader in cancer genome research, is looking for an exceptional candidate to join the Sellers Lab. The successful candidate will join an interdisciplinary team of bioinformatics analysts and biologists who are working together to elucidate new therapeutic hypotheses and to develop novel cancer therapeutics. We employ a range of experimental approaches including large-scale functional genomic screens, chemical biology interrogations, and the elaboration of novel tool compounds, combined with machine learning algorithms and statistical methods in pursuit of improving patient outcomes. We are looking for a candidate who is enthusiastic about taking a hands-on, problem-solving approach, and collaborating with scientist in an informal collegial work environment that is infused with intellectual rigor. The right candidate will have outstanding academic records and strong communication skills, will demonstrate innovative and analytical thinking, and will enjoy working in an interdisciplinary team. Most importantly, we are looking for those who have a deep interest in applying one's analytical and programming skills to developing research tools that help us solve fundamental programs in cancer. CHARACTERISTIC DUTIES Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of large cancer and sequencing data sets. Conceive, implement and test statistical models; work collaboratively and seamlessly with wet-lab researchers to translate these models into testable experiments; analyze the data produced from these experiments. Assist in the analysis of data-rich experiments including those involving RNA-seq, CRISPR and shRNA pooled screens, gain-of-function ORF screens, proteomic data sets, and many others. Explore novel data visualization tools, with emphasis on integrating diverse data types. Implement algorithms as software for distribution to the global cancer research community. Contribute to the writing and data analysis for publications Present at lab meetings, internal Broad scientific meetings, and with time poster and other presentations at external meetings will be encouraged. REQUIREMENTS A Bachelor's or Master’s degree in a quantitative discipline (such as computer science, bioinformatics, physics), or in biology with a strong quantitative background. Fast learner, analytical thinker, creative, "hands-on", highly collaborative team-player. Background in statistics and machine learning is preferred. Proficiency in R and at least one modern programming language, such as Python or C++, is required. Strong communication skills. Knowledge of cancer genomics is a plus, but is NOT required. A strong interest and inclination to acquire such knowledge is a must. #LI-DNP All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
