Job Description:
The Proteomics Platform at the Broad Institute is looking for a motivated post-doctoral associate in computational proteomics. The successful candidate will join an interdisciplinary team of scientists, biologists, clinicians and computational scientists to apply computational, statistical and machine learning methods to advance the state of the art in proteomics. We are looking for individuals who are enthusiastic about taking a hands-on, problem-solving approach, and collaborating with engineers and scientists 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 Proteomics Platform provides the potential for your contributions to be utilized and recognized across a global network of researchers in mass spectrometry-based proteomics. Characteristic Duties: •Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of large proteomics 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 and/or develop novel tools for pathway and network analysis, with emphasis on integrating diverse omics data types. •Implement algorithms as software for distribution to the global cancer research community. Requirements: •Ph.D in Computer Science, Engineering, Math, Statistics, Physics, or a related quantitative discipline. •Experience with Pathway and Network Analysis is REQUIRED. •Practical experience with analytical programming using R, MATLAB, or Python. •Experience with computational analysis, algorithm development and statistics in the context of genomics, proteomics, metabolomics or other -omics data. •Exposure to mass spectrometry-based proteomics and/or computational proteomics is a plus. •A background in biology is not required, though an interest in applying one’s analytical and programming skills to developing research tools is necessary.
Additional Info:
[Click Here to Access the Original Job Post]
The Proteomics Platform at the Broad Institute is looking for a motivated post-doctoral associate in computational proteomics. The successful candidate will join an interdisciplinary team of scientists, biologists, clinicians and computational scientists to apply computational, statistical and machine learning methods to advance the state of the art in proteomics. We are looking for individuals who are enthusiastic about taking a hands-on, problem-solving approach, and collaborating with engineers and scientists 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 Proteomics Platform provides the potential for your contributions to be utilized and recognized across a global network of researchers in mass spectrometry-based proteomics. Characteristic Duties: •Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of large proteomics 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 and/or develop novel tools for pathway and network analysis, with emphasis on integrating diverse omics data types. •Implement algorithms as software for distribution to the global cancer research community. Requirements: •Ph.D in Computer Science, Engineering, Math, Statistics, Physics, or a related quantitative discipline. •Experience with Pathway and Network Analysis is REQUIRED. •Practical experience with analytical programming using R, MATLAB, or Python. •Experience with computational analysis, algorithm development and statistics in the context of genomics, proteomics, metabolomics or other -omics data. •Exposure to mass spectrometry-based proteomics and/or computational proteomics is a plus. •A background in biology is not required, though an interest in applying one’s analytical and programming skills to developing research tools is necessary.
Requeriments :
Skills :
- Bioinformatics
- Computational Biology
- HPC
- Lunix/Unix
- Modeling
- Next Generation Sequencing
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in Java
- Programming in Matlab
- Programming in R
- Statistics
Areas :
Additional Info:
[Click Here to Access the Original Job Post]