Many doctoral application platforms struggle with limited usability and a lack of inclusive design, which can discourage potential applicants. Addressing these limitations is essential, considering the key role doctoral candidates play in driving academic research and innovation. The Technical University of Munich (TUM) has developed TUMApply to support doctoral recruitment, an application portal for open doctoral positions that serves as the central platform for both professors posting jobs and candidates submitting applications. Building on the existing core functionality of TUMApply, this thesis presents the design and implementation of enhancements that improve workflow transparency via comprehensive verification mechanisms, support international applicants through automated grade conversion, and promote inclusive recruitment practices with language analysis tools. These enhancements address identified gaps while maintaining seamless integration with existing platform workflows. The methodology follows a systematic requirements engineering approach incorporating requirements analysis, system modeling, and implementation. The solution adopts a modular architecture that integrates into the existing platform infrastructure, ensuring maintainability and scalability while preserving architectural coherence across system components.