The Broad Institute of MIT & Harvard, a world leader in cancer genome research, is looking for exceptional candidates to join the Cancer Genome Analysis group. The successful candidates will join an interdisciplinary team of bioinformatics analysts, software engineers, genome biologists and clinicians who are working together to identify mutations that lead to cancer, and discover new cancer therapeutics.
We are looking for individuals who are enthusiastic about taking a hands-on, problem-solving approach, and collaborating with engineers and scientist in an informal collegial work environment that is infused with intellectual rigor. The right candidates will have outstanding academic records and strong communication skills, will demonstrate innovative and analytical thinking, and will enjoy working in an interdisciplinary team. The Broad Institute provides a vibrant research environment with close links to MIT, Harvard and the Harvard-affiliated hospitals across Boston. Working in the Broad’s Cancer Program provides the potential for your contributions to be utilized and recognized across the vast global network of researchers in the field of cancer genomics.
• Apply existing and novel algorithms to cancer data sets, analyze data quality, critically review and analyze results, communicate results to biologists, computational biologists, software engineers and clinicians.
• Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of very large cancer data sets, such as The Cancer Genome Atlas project.
• Explore novel data visualization tools, with emphasis on integrating diverse data types
• Implement algorithms as software for distribution to the global cancer research community
• B.S in Computer Science, Bioinformatics, Engineering, Math, Statistics, Physics, or a related quantitative discipline. M.S. degree in same fields is preferred.
• Strong programming skills and experience in algorithm development (using Java, Scala, Python, C++/C#).
• Knowledge of statistics and computational data analysis (R, Python or MATLAB)
• Knowledge of biology/genetics is not required, though it is a plus."
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