TUMApply, the doctoral application portal of the Technical University of Munich, centralizes applications and job postings for a transparent process. However, manual data handling currently leads to inconsistencies, high administrative workloads and reduced clarity for both applicants and professors. This thesis extends TUMApply by introducing AI-supported features that enhance usability. For applicants, the system implements automated data extraction from uploaded documents to prefill profiles and reduce redundant entry. For professors, the system provides AI-based translation suggestions for professors and an enhanced review module to ensure job postings meet all criteria before publication.