Dr Steve Moss

I am a Dad, husband, and PhD. I am a scientist, technologist, and engineer. I am a pugilist, martial artist, and yogi. I love running, swimming, and cycling. I am passionate about science, medicine, research, computing, and all things geeky!

I enjoy coding, gaming, and reading. I am a life-long learner, mentor, and teacher. I am an advocate of open-source software and currently develop in Python, and Go, though I have experience in a number of other languages and am a C programmer at heart. I believe in a free, and open Internet and am an advocate of those rights. I believe in using the power of technology to make the world a better place.

I completed a PhD in Computational Genomics with the EvoHull group at the University of Hull, following on from a BSc (Hons) in Biomedical Science and PGCert in Research Training, also at Hull. I focused on the development of computational methods for large-scale comparisons and analyses of genomic data. The primary focus of my research was to understand the molecular processes that drive changes in genome structure and content over evolutionary time scales. My thesis is available here.

I am most comfortable working with a POSIX-orientated operating system via a command-line interface and feel particularly at home when utilizing my computational skills in a data-intensive environment, whilst collaborating within a multidisciplinary team.

I have eclectic interests across a broad range of topics within the biological, biomedical, clinical, computer, and information sciences, including, but not limited to; anatomy, anthropology, archaeology, bioinformatics, biomedical science, computational biology, cultural evolution, genomics, high-performance computing, infectious diseases, machine learning, medicine, molecular evolution, pathology, phylogenetics, proteomics, scientific computing, social evolution, and infectious/zoonotic diseases. I am also passionate about environmentalism, globalism, humanism, and public health.

My main areas of research focus at present are the application of deep learning algorithms in bioinformatics, genomics and precision medicine.