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This thesis presents two projects related to the genetic diversity of Anopheles mosquitoes. The first project concerns the development and application of sequence based species assignment methods for any species in the genus. The second project discusses the population structure of the major malaria vector Anopheles funestus, with a specific focus on inversions. The ANOSPP amplicon panel is a genus-wide targeted sequencing panel to facilitate large-scale monitoring of Anopheles species diversity. Combining information from the 62 nuclear amplicons present in the ANOSPP panel allows for a more sensitive and specific species assignment than single gene (e.g. COI) barcoding, which is desirable in the light of permeable species boundaries. Here, I present NNoVAE, a method using Nearest Neighbours (NN) and Variational Autoencoders (VAE), which I apply to k-mers resulting from the ANOSPP amplicon sequences in order to hierarchically assign species identity. The NN step assigns a sample to a species-group by comparing the k-mers arising from each haplotype’s amplicon sequence to a reference database. The VAE step distinguishes between closely related species, and also has sufficient resolution to reveal population structure within species. In tests on independent samples with over 80% and 16 % amplicon coverage respectively, NNoVAE correctly classifies to species level 98% of samples within the An. gambiae complex and 89% of samples outside the complex. I apply NNoVAE to nearly 10,000 new samples from Burkina Faso, Gabon, Nigeria and Uganda. In Gabon I found four putative An. arabiensis mosquitoes, a species that was not known to occur in the area. I present the ANOSPP Report Cards, the format used to communicate a summary of the ANOSPP results to the partners who contributed the samples. I also show some additional analyses which can be done using the ANOSPP sequence data, e.g. karyotyping of the 2La inversion. The MalariaGEN Vector Observatory Anopheles funestus Genomic Surveillance Project phase 1.0 dataset (vobs-funestus phase 1.0 for short) consists of whole genome sequence data for 656 samples from 13 different countries in sub-Saharan Africa. Different analysis methods, including PCA, ADMIXTURE and pairwise fixation indices, show that these samples are divided into three primary clusters: one containing specimens from the equatorial region from Ghana in the west to Kenya in the east, and another containing specimens from more southern locations, although here the split between the samples fromnear the east coast and those from near the west coast is more pronounced. There is a small third cluster, separate from the two main clusters, containing only samples from north Ghana. I identify five segregating inversions in this dataset. The positions of three of these, 3Ra, 3Rb and 2Ra, are consistent with previously published genomic coordinates. The other two likely correspond to previously described 3La and 2Rh, based on comparisons to published cytogenetic and microsatellite results. I perform in silico karyotyping for all individuals and identify four putative double recombinant individuals. I characterise the inversion frequencies in their geographical context and identify that all mosquitoes from Benin share the same homozygous inversion state on four inversions, while these states are rare in cohorts from the neighbouring countries. For 2Ra and 2Rh, I present evidence suggesting that the inverted orientation is younger and hence likely the derived one. The 3La inversion shows a pattern consistent with occasional recombination between the different inversion orientations. I consistently observe, in all inversions, a stronger differentiation between the different inversion orientations in the southern cohort compared to the equatorial cohorts, which leads me to speculate that these five inversions originated in equatorial populations., Wellcome Trust