PhD Intern - Computational Biology Advanced Modeling

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Integrated Discovery Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. The Integrated Discovery Sciences Directorate (IDSD) leads fundamental research across biology, chemistry, earth and environmental sciences, materials science, advanced computing, artificial intelligence, quantum information science, mathematics, autonomy, and DOE national user facilities. Our vision is to accelerate scientific discovery by observing, understanding, simulating, predicting, and controlling dynamic biotic-abiotic processes and interactions within complex biological, chemical, material, and Earth systems. We intentionally connect disciplines to advance fundamental discovery science, develop transformative scientific capabilities, and address the nation's most important challenges in energy, environmental resilience, biotechnology, advanced manufacturing, health, and national security.

Responsibilities

PNNL is seeking Ph.D. intern candidates with backgrounds in applied mathematics, statistics, or computational science, and experience with computational modeling in both mechanistic and statistical settings. Selected interns will contribute to modeling and simulation work at the interface of mechanistic and statistical models, with applications in biological and other scientific domains. Ideal candidates will have demonstrated ability to build software from mathematical specifications, with the behavior of each component explicitly specified rather than implicit in the implementation. Source code will be developed within sponsor-directed re