Computational Biologist, Cellularization

United Therapeutics Corporation•Silver Spring, MD

1d•$127,500 - $150,000•Onsite

About The Position

The Computational Lab for In Silico Molecular Biology (CLIMB) is building a computational model of the lung to enable in silico design and testing of lung disease therapies and manufactured organs. As part of this effort to develop an integrative multiscale lung model, the Computational Biologist, Cellularization will apply various mechanistic modeling techniques to simulate molecular and cellular processes. This role involves developing mathematical models of cellular processes in the lung, including cell division, migration, and adhesion, and their modulation by the mechanical and chemical environment. The position will establish an iterative cycle of experimental design based on hypotheses generated by mathematical models to assist with the development of new cellularization approaches. It will also implement procedures for model qualification to evaluate the impact of uncertainty and variability on model output and consequent impact on experimental design. The role requires collaboration with other computational biologists and engineers to integrate cell-based models into large multiscale models and partnering with internal and external labs to understand the needs of experimental scientists and coordinate the generation of experimental data for model training/validation. Effective communication of results through interactive visualizations and presentations, as well as publishing in peer-reviewed journals, is expected. Other duties as assigned.

Requirements

Master’s Degree in biomedical engineering, computational biology, applied mathematics, or related field of study and 6+ years of industry experience developing computational models of biological systems with a master's degree OR 2+ years of industry experience developing computational models of biological systems with a PhD. Postdoctoral experience at a pharmaceutical/biotech company is acceptable
Expertise in one or more modeling frameworks for cell-level behavior (e.g. agent-based models, cellular Potts models, etc.)
Expertise in numerical methods relevant to modeling and simulation, including solving systems of ordinary and/or partial differential equations, optimization, Monte Carlo methods
Fluency in one or more scientific programming languages (e.g. Python, R, Julia)
Experience with cell-based modeling and simulation software packages (e.g. Morpheus, CompuCell3D)
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

Nice To Haves

Doctor of Philosophy (PhD) in biomedical engineering, computational biology, applied mathematics, or related field of study
Familiarity with quantitative systems pharmacology and other applications of modeling and simulation within pharmaceutical drug discovery and development
Skilled in statistical and machine learning methods
Knowledge of pulmonary physiology

Responsibilities

Develop mathematical models of cellular processes in the lung, including but not limited to cell division, migration, and adhesion, with modulation by the mechanical and chemical environment based on published models and extensions developed in-house to analyze experimental data from cellularization of 3D-printed scaffolds with endothelial, epithelial, and other cell types
Establish iterative cycle of experimental design based on hypotheses generated by mathematical models to assist with development of new cellularization approaches
Implement procedures for model qualification to evaluate impact of uncertainty and variability on model output and consequent impact on experimental design
Collaborate with other computational biologists and engineers to integrate cell-based models into large multiscale models spanning processes from organ to molecular level
Partner with internal and external labs to better understand the needs of experimental scientists and coordinate the generation of experimental data for model training/validation
Communicate results effectively through interactive visualizations and presentations at internal and external meetings and publishing in peer-reviewed journals
Perform other duties as assigned