Associate Director, Biosimulation

We are seeking an expert in systems biology and modeling to lead a team of scientists developing computational tools for modeling systems biology especially in the field of pharmacokinetics, pharmacodynamics, efficacy, and associated upstream and downstream models. They will be responsible for the growth and development of the team and technical efforts to increase the capabilities of our proprietary computational drug development platform. The ideal candidate is a lifelong learner who is excited and willing to learn about AI/ML and the drug development process and can succeed in an innovative, fast-paced, high-intensity startup environment.

Key responsibilities:

- Lead the direction of modeling & simulation efforts, and create a unified strategy for the scientific team including monthly/quarterly goals.

- Manage and mentor scientists in computational chemistry, biology, model development.

- Develop processes enabling the efficient translation of scientific research into computational models and robust software

- Apply modeling/drug development expertise and understanding of core physiological mechanisms to the development of pharmacological computational models

- Collaborate with the sales team to present technology and vision to customers and internal stakeholders

- Conduct feasibility evaluations and planning for client projects

- Conduct independent research on modeling approaches, and define course-of-action for translation of novel scientific research into modeling workflows

- Contribute to scientific manuscripts and grant proposals that demonstrate the utility of the computational platform

Qualifications:

- Ph.D. or equivalent degree in engineering, PK / PK-PD / Agent-based modeling & simulation or related life science discipline

- 5+ years of experience implementing mathematical models to solve complex biological problems, preferably in the pharma/CRO space or startup environment

- Publication record applying systems modeling approaches to biological systems

- Excellent leadership and interdisciplinary communication with strong time management and planning skills and the ability to thrive in ambiguity

- Experience with data analysis: regression, statistics, and classification algorithms.

- In-depth knowledge of numerical methods, optimization, and programming (e.g. Matlab, C, and Python). Experience with machine learning methods is a plus.

- Experience in a client-facing or client-supporting technical role translating customer requests into design requirements