Job Description:
Job Description The Proteomics Platform at the Broad Institute (Steve Carr PI) is looking for a motivated post-doctoral associate in computational proteomics who will focus on developing and applying innovative computational approaches to analyzing proteogenomics data spanning genomics transcriptomics proteomics phosphoproteomics and other posttranslational modifications from cancer cardiovascular and other diseases being actively studied at Broad. The work will involve analysis of large-scale multi-omics data via pathway and network analysis integrated with statistical and machine learning approaches to derive biological insights and identify therapeutic opportunities. The successful candidate will be part of an interdisciplinary team of proteomics and computational scientists biologists and clinicians. He or she will apply computational statistical and machine learning methods to advance the state of the art in proteomics; develop data analysis strategies write algorithms and deploy computational tools for the exploration of large proteogenomics 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; test and develop novel tools for pathway and network analysis with emphasis on integrating diverse omics data types; and implement algorithms as software for distribution to the global research community. Requirements: - The candidate should have a Ph.D in Computer Science Bioinformatics Computational Biology Statistics or a related quantitative discipline. We are specifically looking for a talented and motivated researcher with a proven track record in applying computational methods to the analysis of large-scale omics datasets.
- A strong background in statistics and machine learning with both breadth of knowledge (hypothesis testing linear models supervised and unsupervised learning methods) and depth in a specific area (e.g. pathway and network analysis Bayesian analysis probabilistic methods deep learning).
- Proven programming skills with the ability to learn new languages and environments quickly. The group primarily uses R and Python along with shell scripts and other languages as needed in a cluster and cloud computing environment.
- Exposure to mass spectrometry-based proteomics and/or computational proteomics is a strong plus.
- Excellent ability to learn quickly and strong problem-solving skills along with effective communication are essential to successful performance in the fast-changing research computing environment at the Broad Institute.
The Broad Institute provides a vibrant research environment with close links to MIT Harvard and the Harvard-affiliated hospitals across Boston. Working in the Broads Proteomics Platform provides the potential for your contributions to be utilized and recognized across a global network of researchers in mass spectrometry-based proteomics and proteogenomics. The Proteomics Platform is currently a significant contributor to many large consortium projects including the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Molecular Transducers of Physical Activity Consortium (MoTrPAC) among others with flagship publications in high profile journals. Interested candidates should send a letter of inquiry and CV to Steven Carr (scarr@broad.mit.edu) and to D. R. Mani (manidr@broad.mit.edu). All Broad employees regardless of work location must be fully vaccinated for COVID-19 by Tuesday October 12 2021. Requests for exemption for medical or sincerely held religious beliefs will be considered. #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. EEO is The Law - click here for more information Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled Check out this video for a look into our community! |
