Broad Institute

The Broad Institute of MIT and Harvard is one of the world's leading biomedical research institutes. It seeks to discover the molecular basis of major human diseases, develop effective new approaches to diagnostics and therapeutics, and disseminate discoveries, tools, methods, and data openly to the entire scientific community. Founded in 2004, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities, with collaborations spanning the globe. 

Our lab’s mission is to uncover biological knowledge by developing advanced methods to quantify and mine the rich information in images. We love working as a team towards scientific goals: discovering the inner workings of biological systems and influencing patient treatment. We love making open-source software that impacts the world. We are conscientious and enjoy a professional, no-fuss environment, and are passionate about what we do while frowning on workaholism. 

Want to devote your expertise in data science to accelerate the pace at which new medicines are found? Our laboratory develops and applies methods for extracting quantitative information from high-throughput biological images. We are well-known for creating the open-source CellProfiler software, used by scientists around the world to quantify biological processes in images. Cited in 15,000+ scientific papers, it has led to potential therapeutics, including several successful clinical trials in cancer. 

 We seek a researcher to join our efforts to glean insights from large collections of images. There is much more information present in microscopy images than is commonly perceived by eye. We harvest this information, developing novel methods to characterize cellular populations at single-cell resolution. This work has the potential to transform how both the targets and therapies for disease are identified. 

 We aim to revolutionize the process of drug discovery in several projects, including: 

• Identifying the function of unknown genes and predicting mutation impact, for personalized medicine 
• Predicting how new chemical compounds act in cells 
• Repurposing existing drugs to new diseases 
• Identifying new therapies for bipolar disorder or depression, based on cell morphology changes 
• Predicting and classifying toxicity of compounds destined for clinical trials 

Over the last few years, we developed Cell Painting, the leading image-based profiling assay, wrote review articles about the field, created an organization (CytoData Society) to build and maintain an active community, including hosting an annual symposium and hackathon, now in its seventh year running (featured in Science), hosted the 2018 Data Science Bowl which was the largest Kaggle competition for social good in history. We launched a consortium with ten pharmaceutical companies to create the world’s largest Cell Painting dataset of >2 billion cells responding to over 170,000 small molecules and genetic perturbations. We demonstrated that profiling can illuminate novel connections between genes, published papers building the foundation for using deep learning for profiling, and developed software libraries for supporting this research. 

• Ph.D. required, in a quantitative discipline such as Computer Science, Bioinformatics, Computational Biology, Physics, or Math. 
• Large-scale data analysis experience is required, as is enthusiasm for biology/biomedicine. 
• Must demonstrate outstanding personal initiative, organizational ability, communication skills, and teamwork.

In your cover letter, please describe your overall career interests, why this work would suit you, and what you would aim to learn. Please include specific examples of data analysis projects you have undertaken, including links to sample Python/R notebooks demonstrating your skills. Starting stipend ranges from $66,000-72,000, depending on years of experience post-PhD.