Deep Origin is seeking a Machine Learning Scientist to join our team. In this role, you will focus on creating machine learning-based representations of biological systems and tuning composite models to build a multiscale biological simulator for drug response prediction. You will collaborate closely with the Cellular Simulations team to integrate biological simulations into machine learning approaches.
What You'll Do
- Construct ML-based representations of biological systems, in particular signaling pathway dynamics in cells.
- Help to create a hybrid multiscale biological simulator, incorporating ML components for more effective model calibration and simulation.
- 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.
What We're Looking For
- B.S. or M.S. in a relevant quantitative field (Computer Science, Math, Physics, etc.).
- At least 2-3 years of experience in the development of machine learning models in an industry setting.
- Knowledge of optimization methodologies for machine learning models.
- Some experience with ML applications in biology.
- Extensive coding experience, preferably Python, but other language proficiency will be considered depending on experience.
- Fluent English for collaboration with an international team.
- Ability to work on US time zones when needed.
Nice to Have
- Ph.D. in a relevant field.
- Deep experience in biological modeling and simulation, in particular in a systems biology or molecular level context.
- Experience with ML tasks involving small datasets.
- Experience in optimization of 'composite models' - connected models that share output/input.
Work Mode
This is a global role.
