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This thesis is concerned with improving and expanding projection based methods for Hermitian interior eigenvalue problems. The focus is on methods of this type utilizing a rational function based filtering approach. We outline various strategies and novel variations to improve the efficacy of these methods and their suitability for solving large sparse eigenvalue problems. The potential for improvement is shown in numerical experiments.