Statistical modelling of natural selection based on deoxyribonucleic acid (DNA) data is the research field that primarily interests me. Molecular evolutionary studies offer effective methods for using DNA genomic information to investigate biomedical phenomena. Phylogenetics – the study of the evolutionary relationships among living organisms using genetic data – is one of those methods. Natural selection is an aspect of phylogenetics that has gained significant research attention. It includes the use of theoretical probability techniques to identify genetic loci that are crucial to the survival of living organisms. One utility of natural selection analyses is in the understanding of how pathogens evade treatments and the immunity of their hosts. Given the lack of cure for some existing pathogens such as HIV and the continuous outbreaks of new pathogens such as the coronavirus, natural s​election remains an ever exciting research field. Selection has traditionally been studied as a measure of relative fitness among alleles in the field of population genomics. As a result, there exists a good volume of theoretical work in the population genomics literature. This rich body of work is yet to be fully synchronised with phylogenetic research due to mathematical complexities. Therefore, I am specifically keen on bridging the gap between the population genomic and phylogenetic fields with respect to Darwinian natural selection.