Oak Ridge National Laboratory - Oak Ridge, TN
posted 7 months ago
Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, dedicated to conducting both basic and applied research to deliver transformative solutions to pressing challenges in energy and security. We are currently seeking a Postdoctoral Research Associate to join the Computational and Predictive Biology Group within the Biosciences Division (BSD) at ORNL. This division is committed to advancing science and technology to enhance our understanding of complex biological systems and their interactions with the environment. The BSD possesses specialized expertise and facilities in various fields, including genomics, computational systems biology, microbiology, microbial ecology, biophysics, and structural biology. The role of the Postdoctoral Research Associate will involve engaging in computational systems biology research, which encompasses the development and application of methods to analyze large-scale omics, greenhouse, field, and clinical datasets. The goal is to derive insights and hypotheses that can be further validated through experimental work, thereby enhancing researchers' capabilities to deepen their understanding of biological systems. This position is critical as it supports various projects at ORNL, including those funded by the Department of Energy (DOE), National Institutes of Health (NIH), Veterans Affairs (VA), and the National Science Foundation (NSF), among others. The successful candidate will contribute to the development of systems biology approaches, explainable AI, network analysis, and information flow. In this position, you will be responsible for the development and support of data collection, modeling, and integration, as well as the associated computational and machine/deep learning environments and interfaces for systems biology. You will analyze large biological datasets to construct accurate predictive models of biological processes and publish original research findings. Collaboration with both internal and external researchers will be essential to analyze and interpret novel results using newly derived methods. Additionally, you will contribute to ongoing projects within the group and will have the opportunity to define and develop your own projects.