Summary: Deep Origin is seeking a Modeling and Numerical Optimization Specialist to construct and optimize large-scale biological simulation and parameter optimization approaches for whole-human toxicology predictions. Highlights: 1. Accelerate drug discovery through AI-powered tools 2. Develop cutting-edge simulation and optimization approaches 3. Work on large-scale biological models for toxicology predictions 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 modeling and numerical optimization specialist with experience working in Systems Biology, Quantitative Systems Pharmacology, and/or Toxicology. You will help to construct simulation and parameter optimization approaches for large\-scale systems of biological models, which include mechanistic and machine learning model components, used in whole\-human toxicology predictions. Additionally, you will work on efficiently simulating and optimizing the system of models at scale, including using high performance computing and distributed computing frameworks. **Requirements** * Bachelor's or Master's in a relevant quantitative field (Biology, Computer Science, Math, Physics, Engineering, etc.). * Experience in construction and parametrization of biological models, either ML or mechanistic. * Extensive coding experience in Python. * Experience with high\-performance computing and/or distributed systems. * Experience with optimization algorithms and numerical considerations. * Experience with classical ML approaches, such as tree\-based methods, MLPs, etc. **Responsibilities:** * Construct software frameworks for seamlessly connecting, executing, and parametrizing large\-scale systems of biological models, ranging from physiological to molecular scale. * Work with the Deep Origins Cellular Simulations team and the wider company to develop interfaces for sub\-models at various scales, which represent biological processes relevant to physiology and toxicology, to incorporate into the above framework. * Incorporate interpretable machine learning methods in the system of models, where appropriate, to help capture unrepresented interactions and calibrate to experimental or clinical outcomes. * 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. **Nice to have:** * Experience with cellular pathway or organ modeling, for purposes of drug discovery or toxicology. * Experience with creating surrogate models of biological systems, with analytical or ML\-based approaches. * Experience with interpretability and sensitivity analysis of mechanistic and machine learning models. * Experience with GPU computation, C, and C\+\+.
David Muñoz
Indeed · HR
David Muñoz
Indeed · HR
