Our Computational Lab for In Silico Molecular Biology (CLIMB) in Silver Spring, Maryland is building a computational model of the lung to enable in silico design and testing of therapies for lung disease. As part of this effort to develop an integrative multiscale lung model, we are looking for a Computational Biologist to join our CLIMB team. In this role, you will apply various modeling techniques to simulate molecular and cellular processes, focusing on their impact on lung physiology and pharmacology.
- Develop mathematical models of molecular and cellular processes in the lung, including but not limited to regulation of vasoconstriction and bronchoconstriction, response to hypoxia, toxicity to airways/alveoli, and initiation/resolution of inflammation and fibrosis
- Conduct research into approaches for mechanistic modeling of biological processes and determine suitability for specific applications
- Integrate diverse data sources, including large-scale genomic and transcriptomic assays, into model development and calibration workflows
- Implement procedures for model qualification to evaluate impact of uncertainty and variability on model output
- Collaborate with other computational biologists and engineers to integrate models into large multiscale models spanning processes from organ to molecular level
- Partner with internal and external labs to generate experimental data for model training/validation
- Communicate results effectively through interactive visualizations, presentations at internal and external meetings, and peer-reviewed publications
Minimum Requirements:
- Master’s or Ph.D. degree in biomedical engineering, computational biology, or related field of study
- 2+ years of industry experience developing computational models of biological systems
- Fluency in one or more scientific programming languages (e.g. Python, R, Julia, and/or MATLAB)
- Expertise in one or more modeling formalisms for systems biology (e.g. differential equation, logic-based, or agent-based models)
- Familiarity with quantitative systems pharmacology and other applications of modeling and simulation within pharmaceutical drug discovery and development
- Expertise in numerical methods relevant to modeling and simulation, including solving systems of ordinary and/or partial differential equations, optimization, Monte Carlo methods
- Experience with common databases and tools relevant to bioinformatics and systems biology
- Knowledge of molecular and cellular biology and drug development
- Ability to communicate effectively with both technical and non-technical audiences as demonstrated by record of presentations and publications
Preferred Qualifications:
- 6+ years of industry experience developing computational models of biological systems Postdoctoral experience at a pharmaceutical/biotech company is acceptable
- Experience processing and analyzing large-scale genomic and transcriptomic datasets
- Strong data visualization skills, including interactive visualization (e.g. R Shiny or d3.js)
- Skilled in statistical and machine learning methods
- Knowledge of pulmonary physiology
Apply through the link