Associate Director, Computational Biology

California, US residents click here.

The job details are as follows:

Who We Are

We are the first publicly-traded biotech or pharmaceutical company to take the form of a public benefit corporation. Our public benefit purpose is to provide a brighter future for patients through the development of novel pharmaceutical therapies; and technologies that expand the availability of transplantable organs.
 

United Therapeutics (Nasdaq: UTHR) seeks to travel down the corridors of indifference to develop treatments for rare, deadly diseases. We were founded in 1996 by a family seeking a cure for their daughter’s pulmonary arterial hypertension (PAH). Today, we have six FDA-approved therapies that treat PAH, pulmonary hypertension associated with interstitial lung disease (PH-ILD) and neuroblastoma, a rare pediatric cancer. Our near-term pipeline seeks to develop additional therapies for PAH and pulmonary fibrosis (PF).
 

The cure for end-stage life-threatening diseases like PAH, PH-ILD, PF, and many others is an organ transplant, but only a small percentage of donated organs are available to address the vast need. For this reason, we are working to create manufactured organs to address the shortage of kidneys, hearts, lungs, and livers available for transplant. We believe an unlimited supply of tolerable, transplantable organs will eliminate the transplant waiting list and cure end-stage organ diseases for which transplant is not currently an option.

Who You Are

The Computational Lab for In Silico Molecular Biology 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, the Associate Director, Computational Biology will apply various modeling techniques to simulate molecular and cellular processes, focusing on their impact on lung physiology and pharmacology. This role contributes to the development and evolution of computational modeling strategy, ensuring alignment between technical direction, research priorities, and model-informed drug development across programs.

• Lead teams in strategically planning and implementing mechanistic 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
• Provide expertise in evaluating innovative approaches for mechanistic modeling, informing technical direction and prioritization for areas such as AI-enabled model development, multiscale coupling, in silico trials, and regenerative medicine
• Define, evolve, and execute a technical strategy in partnership with other internal subject matter experts to apply model-informed drug development throughout the company
• Build and manage collaborations with external partners to generate data for model training/validation
• Coordinate teams of computational biologists and engineers to build HPC workflows for multiscale models that bridge organ physiology with cell- and molecular-level processes
• Advance company-wide uptake of computational modeling by leading development of simulation tools and interfaces in partnership with leaders in other R&D departments
• Communicate results through presentations at internal and external meetings, and peer-reviewed publications
• Direct and manage team to include responsibilities for goal setting, performance reviews/management, coaching, mentoring and career development
• All other duties as assigned

For this role you will need

Minimum Requirements

• Doctor of Philosophy (PhD) in engineering, applied mathematics, systems biology, or related field of study
• 7+ years of experience in mechanistic modeling approaches in the pharmaceutical industry
• Experience leading, developing, and mentoring team members, with demonstrated ability to build capability and support professional growth
• Experience with common databases and tools relevant to bioinformatics and systems biology
• Expertise in a variety of modeling formalisms for systems biology (e.g., differential equation, logic-based, or agent-based models)
• Expertise in pharmaceutical modeling and simulation approaches (e.g., quantitative systems pharmacology (QSP) or physiologically-based pharmacokinetic (PBPK) modeling)
• Advanced knowledge of numerical methods relevant to modeling and simulation, including solving systems of ordinary