Flexible proteins, such as monoclonal antibodies are widely used platforms for treating disease. However, the complexity of their structure makes generating actionable predictions of critical quality attributes (CQAs) difficult. True advancement in making these predictions requires a shift in understanding the problem, from a single-structure representation to using ensembles of structures as the best predictors of experimental data. This requires a bottom-up reimagining of many different methodological assumptions, that are currently based around simple single conformations of globular proteins. To address this gap, molecular dynamics (MD) simulations and Neutron Scattering will be used to perform structural characterization of flexible proteins, such as monoclonal antibody therapeutic drug platforms. The postdoctoral researcher will create computational models that integrate structural predictions and neutron scattering data using ensembles instead of current single structure implementations. The integration of simulation and experiment will yield methods that can be applied to large biopharmaceutical products or platforms, and change the way scientists fundamentally deal with these types of data and biological systems.