The Computational Lab for In Silico Molecular Biology (CLIMB) applies computational modeling to enable in silico design and testing of therapies for lung disease. As part of this effort to develop an integrative multi-scale lung model, the Data Scientist – Computational Biology will analyze and integrate diverse data types, including molecular, imaging, and text-based (scientific publications) to map biological processes relevant to lung disease pathogenesis and treatment.
- Analyze and interpret high-dimensional molecular datasets, both public and internal, to identify biological processes/pathways relevant to lung physiology and pathology and apply this information to discover drug targets and infer mechanism of action.
- Conduct research into suitable machine learning approaches for deriving insights from molecular datasets through gene regulatory network inference, dimensionality reduction, clustering, or supervised learning.
- Apply natural language processing techniques to extract relationships among biological processes from literature sources.
- Integrate biological knowledge from diverse sources, such as pathway databases, protein interaction networks, ontologies, and functional assays, to enhance interpretation of molecular datasets.
- Communicate results effectively through interactive visualizations, presentations at internal and external meetings, and peer-reviewed publications.
Minimum Qualifications
- Bachelor’s degree in computational biology, applied mathematics or related field of study
- 6+ years of industry experience with a BA/BS
- 4+ years of industry experience with a MA/MS
- 2+ years of industry experience with a PhD
- 1+ year experience with common databases and tools relevant to bioinformatics and systems biology
- Expertise in statistical and machine learning methods applied to high-dimensional molecular datasets, text mining, and/or imaging data
- Fluency in one or more scientific programming languages (e.g. Python, R, Julia, and/or MATLAB)
- Ability to communicate effectively with both technical and non-technical audiences as demonstrated by record of presentations and publications
Preferred Qualifications
- Master’s degree in computational biology, applied mathematics or related field of study
- Doctor of Philosophy (PhD) in computational biology, applied mathematics or related field of study
- 1+ year experience with imaging (CT, MRI) data
- Knowledge of molecular/cellular biology, pulmonary, physiology, and drug development
- Strong data visualization skills, including interactive visualization (e.g. R Shiny or d3.js)
- Proficiency with deep learning software packages