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Quantitative Systems Pharmacologist / Systems Biology Scientist at Deep Origin. Deep Origin. is a biotechnology company accelerating drug discovery through AI-powered tools. Our platforms simplify R&D, simulate biology, and empower scientists to solve diseases and extend healthspan.. We are looking to recruit a Scientist with experience applying Systems Biology modeling and concepts in a Quantitative Systems Pharmacology/Toxicology context. You will construct organ and tissue models that connect molecular-level interactions to physiological and toxicological end-points and outcomes. . PhD in Bioengineering, Biotechnology, Systems Biology, QSP/PKPD, Systems Pharmacology, etc. . . 2 or more years postdoctoral or industry experience constructing systems biology and related models in a QSP/QST context. Particularly in one or more of Liver, Intestine, Kidney, Blood, and Bone marrow. . . Extensive experience in Python (at least 3 years). . . Experience with SBML (2 years). . . Fluent English for collaboration with an international team.. . Be able to work on US time zones when needed.. . Nice to haves:. Deep knowledge of available datasets to inform QSP/QST models. . . Experience deploying models in an HPC environment. . . Experience in model parameter optimization. . . Experience in virtual population generation. . . Composite model construction, parameterization, and simulation. . . Responsibilities:. . Construct Systems Biology-oriented QSP/QST models that capture molecular interactions and link these to physiological and toxicological outcomes and phenotypes. . . Work with the Deep Origins Cellular Simulations team and the wider company to interface these models with larger-scale intracellular models and multi-scale models of biological processes relevant to physiology and toxicology. . . Plan and organize work to ensure specific deadlines and milestones are met, coordinating with others to ensure work is correctly aligned and integrated with other efforts. . . Communicate effectively within the company and external teams, updating others frequently on progress and bottlenecks. . . Company Location: United States.