Vacancies, recognized as intrinsic defects, play pivotal roles in modulating the structural and electronic behavior of materials. This significance becomes particularly evident in the context of niobium nitride (NbN). NbN can accommodate a substantial number of vacancies across both its sublattices. The distribution, density, and configuration of these vacancies have the potential to influence the inherent attributes of the material greatly. In light of this understanding, this proposal sets forth a plan for a systematic exploration of potential vacancy ordering within NbN. To realize this objective, the proposal suggests using the capabilities of Quantum ESPRESSO, known for its effectiveness in simulating complex material systems. By employing rigorous density functional theory (DFT) calculations, the aim is to uncover diverse vacancy configurations and to evaluate their impact on the macroscopic properties of NbN. Given the computational demands of such an investigation, this proposal makes a straightforward appeal for the allocation of advanced supercomputing resources. With the right computational backing, the research is aimed to provide in-depth insights into the role of vacancies in NbN.