Job Description The Broad Institute is an amazing place - we apply our deep knowledge of human genetics to empower a revolution in biomedicine and accelerate the pace at which the world conquers disease. Through our partnerships with MIT, Harvard, and the Harvard teaching hospitals, we've become a worldwide hub of cutting-edge biomedical science. The Broad was founded to explore the applications of genomic medicine, and now conducts research in infectious disease, cancer, and inherited disease, along with basic research in the life sciences. The Broad is looking for exceptional candidates to join the Cardiovascular Disease Initiative (CVDi). The successful candidates will join an interdisciplinary team of computational biologists, laboratory scientists, and clinicians working together to identify and validate new molecular targets for cardiovascular disease, with the ultimate goal of advancing novel therapeutics to the clinic in collaboration with a strategic industry partner. We are looking for a researcher to take initiative on the development of solutions to preprocess and analyze high throughput cell imaging data aimed towards increasing our mechanistic understanding of disease and potential novel therapies. We want to harvest this information through morphological profiling, developing novel methods to characterize cellular populations at single-cell resolution to discover similarities and differences among cell treatments. The candidate will perform analyses of single-cell high content imaging data and collaborate directly with scientists performing experimental research studies at the bench. Example work streams include: Expertise in advanced quantitative image analysis, with software such as CellProfiler Experience with morphological profiling and familiarity with RNA sequencing data (preferred) Experience with the R/Python data stack (numpy, pandas, sklearn, etc) A good grasp of the fundamentals of probability, statistics, and machine learning Prior experience of developing and implementing analyses of high-throughput microscopy/large-scale image data to address biological questions Familiarity with working on an interdisciplinary project team, contributing to experimental design analyses in collaboration with biologists and chemists Demonstrable examples of development of reproducible software tools in collaboration with other data scientists and biologists Excellent communication skills and an ability to operate in a multi-disciplinary research environment Collaborate with other machine learning scientists and data engineers to develop scalable solutions for data analyses and visualization Design and lead independent projects Create scientifically rigorous visualizations, communications, and presentations of results Contribute to generation of protocols, publications, and intellectual property Maintain and organize computational infrastructure and resources REQUIREMENTS Ph.D. in a quantitative discipline such as computational biology, bioinformatics, computer science, statistics, mathematics, physics, or related field preferred, but talented applicants of all levels are encouraged to apply Machine learning and/or large scale data analysis experience is required, as is enthusiasm for biology or biomedicine Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent), and a programming language (C/C++, Java) Track record of working on complex problems, and ability to integrate data from multiple disciplines Strong interpersonal, influencing, and collaboration skills to work in a team-oriented, matrix environment, and the ability to work through conflicts Must demonstrate outstanding personal initiative, communication skills, and the ability to work effectively as part of a team Outstanding verbal and written communication abilities Ability to adapt to and effectively manage changes in a fast paced and dynamic environment A passion for science and sense of urgency to find new medicines to benefit patients
