Malaria remains a leading cause of illness and death worldwide, particularly in sub-Saharan Africa, which bears the majority of malaria-related morbidity and mortality. While first-generation malaria vaccines represent a significant advance, their modest and time-limited efficacy underscores the need for improved vaccine strategies. Progress is impeded by the complex immunological landscape governing protection against Plasmodium falciparum infection and disease, as well as the parasite’s extensive antigenic diversity which has evolved to evade host immunity through antigenic escape. In this study, I applied high-throughput serological profiling to identify correlates of protection following whole-organism vaccination and implemented temporally informed population genetic analyses to detect immune-driven antigenic escape. Proteome-wide IgG reactivity (>3.9 million 16-mers) was measured using sera collected before and after PfSPZ vaccination from individuals later challenged by controlled human malaria infection. Although vaccination induced broad serological responses across more than 4,000 proteins, few peptide-level responses were associated with protection. Most differentially reactive peptides were elevated in unprotected individuals both before and after vaccination. Pre-vaccination differences may reflect preexisting cross-reactive antibodies. After vaccination, protection-associated targets were enriched for membrane-localized proteins, while peptides elevated in unprotected individuals were linked to nuclear processes. These findings suggest that linear peptide reactivity alone may be insufficient to define correlates of protection and that additional immune mechanisms are likely to contribute. To investigate antigenic escape, I analyzed whole-genome sequence data from clinical isolates collected over 15 years from symptomatic infections in southern Malawi. Using Tajima’s D and Hudson’s FST across sliding genomic windows, I identified 21 genes showing consistent signals of balancing selection and temporal allele frequency shifts. One identified gene, PF3D7_0710200, encoding a conserved protein of unknown function, underwent further analysis using both supervised and unsupervised machine learning to identify key amino acid residues and haplotype clusters. Random forest analysis identified nine informative amino acid residues that delineated four major haplotypes that remained stable over time, with three accounting for over 90% of circulating diversity. These findings support the integration of immunological and evolutionary approaches to inform vaccine design and identify promising targets for broadly protective malaria vaccines.