The Broad Institute of MIT & Harvard is looking to hire an exceptional candidate to join an initiative whose goal is to translate cutting-edge genomics into novel therapeutics. The successful candidate will join an interdisciplinary team of computational biologists, genome biologists and clinicians who are working together to understand how genes that normally protects us, can turn our immune system against us. Gaining such an understanding will allow us to identify therapeutic leads that can subvert autoimmune and inflammatory processes and potentially help diabetic patients, for example.
We are looking for individuals who are enthusiastic about taking a hands-on, problem-solving approach, and collaborating with engineers and scientists in a collegial environment that is infused with intellectual rigor. The successful candidate will be an innovative and analytical thinker, 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. Being a member of our initiative will provide the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and chemical biology.
- Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of large data sets.
- Conceive, implement and test statistical models; work with wet-lab researchers to translate these models into testable experiments; analyze the data produced from these experiments.
- Explore novel data visualization and text-mining tools with an emphasis on integrating diverse data types.
- Implement algorithms and develop software for application in disease pathway discovery.
- B.S in Computer Science, Engineering, Math, Statistics, Physics, or a related quantitative discipline
- Practical experience with programming languages Java and C; and analytical programs MATLAB, R, or Python
- Experience with computational analysis, algorithm development and statistics
A background in biology is not required, though an interest in applying one’s analytical and programming skills to developing research tools is necessary.
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