Scientist, Modeling and Optimization

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 seeking a Modeling & Numerical Optimization Specialist to join our team at the forefront of computational life sciences.

In this role, you will help to construct simulation and parameter optimization approaches for large-scale systems of biological models, including 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.

If you have a strong background in Systems Biology, Quantitative Systems Pharmacology, and/or Toxicology, and you’re excited to solve highly complex, real-world biological challenges using cutting-edge computational methods, we’d love to connect with you.

• 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++.