I am a University of Oxford PhD graduate that has worked within computational genomics for over 8 years. During my time at the Big Data Institute I specialised in machine learning using genetic data from bacteria, but I previously also worked with human, insect and viral data. As the COVID pandemic hit I changed over to risk factor analysis in a Bayesian framework using the vast heterogeneous data from the 500,000 UK Biobank participants. During my past academic career I was first author (3), co-author (2) or part of an author cosortium (6) on 10 publications, published in journals like Nature, The New England Journal of Medicine, Nature Ecology and Evolution, Cell reports and Microbial genomics.
I have always been fascinated by the extent of information lying at the fingertips of those willing to dive deep into the wealth of genetic data. In my work I combine skills from genomics, computer science, machine learning and applied statistics to generate applicable insight utilising high performance computational environments. After finishing my doctoral degree I wanted to grow my skills on more applied challenges, like helping alleviate the burden of disease using bottom up data-driven solutions. Examples of my code can be found on my GitHub.
In my work I use Python and R to adjust input and output for existing tools and also develop standalone programs. I implement and combine own scripts with existing programs in Bash to form streamlined pipelines which can be run on clusters via Sun Gridengine and SLURM or on cloud computing platforms like AWS. My pipelines and their output are accompanied with statistics, manuals, reports and work-flows generated by R, Matlab, Inkscape and LaTeX.
Outside of pure research I also took over responsibilities in teaching, having demonstrated and lectured on courses like advanced python, statistical genetics, html, LaTeX and bash. Together with two other doctoral candidates we conceived a neural networks crash course for our fellow D. Phil student. The course ran over 3 separate days with theoretical lectures and programming practicals. I developed and led the recurrent neural networks part of the course. During my Masters degree I also supervised two fellow MsC students on a project related to computationally analysing protein characteristics. In my spare time I like to play Basketball, having played for the University of Oxford team for many years during my degree. Also having worked for a cinema during my undergraduate I became a keen cinophile alongside my eternal love for reading.
October 2017 - July 2022
I was enrolled in the Interdisciplinary Biosciences Doctoral Training Partnership at the Doctoral Training Centre in Oxford. My program consisted of 3 months of courses followed by 2 12-week rotations, an internship and a 3 year PhD project.
My two rotations were about endogenous viral elements in insects and using machine learning to trace the source of campylobacteriosis.
These were the chapters of my thesis:
The research going into my first results chapter was published in PLOS Genetics. The COVID work that the last results chapter is based on, led to multiple consortium authoships as part of the COVID-19 Host Genetics Initiative among which are publications in The New England Journal of Medicine, Nature and Cell reports. For a project I could not pursue due to COVID, I also wrote a review on bacterial paleogenetics for Microbial genomics.
During my PhD I was part of the Blues Basketball University Team.
October 2014 - October 2016
I did my Master's at the University of Muenster, taking part in the special study program evolution. My masters consisted of a year of course-work, where I took classes in statistics, advanced Python and population genetics. The second year was fully taken up by my thesis work, where I was working on genome assembly and annotation within the Blatella germanica sequencing project. Our work culminated in a publication in Nature Ecology and Evolution I was co-author on as well as publication in Journal of Experimental Zoology I have shared first authorship on. To prepare for the project I also contributed to a review in Current opinion in Insect Science.
During my MSc I also did an internship at the Michael Smith Laboratories at the University of British Columbia, working on ancestral sequence reconstruction within the dimethylenzimidazole synthesis pathway in close collaboration with wet lab scientist.
Outside of studying I was part of the organising committee of Erasmus Muenster, helping students abroad settling into their new environments. I also taught in the Python course and supervised two fellow Master students on a project concerning computational gene analysis.
October 2011 - October 2014
I did a general Bacherlor in Biological sciences, which features many biological, biochemical, mathematical, statistical and practical wet lab courses. As wet lab work was not among my strengths and I found the bioinformatics module fascinating, I decided to do my Bachelor thesis within the molecular evolution and bionformatics group ofprofessor Bornberg-Bauer. After an inital Python course, I spend the 6 months writing pipelines to analyse the characteristics of de novo proteins.
In the fifth semester of the course I spent an Erasmus semester at the University of Sheffield, where I played for the university team.
Since October 2022
I am currently employed as a health data scientist to finish a project wherein we use Bayesian model averaging for COVID risk factor analysis based on a broad range of health descriptors drawn from the complete set of UK biobank data.
June 2018 - July 2022
The DTC Coding Dojo is a network of peer support within the Doctoral Training Centre at the University of Oxford. Anyone with a bioinformatics related problems can get it solved with the help of an expert panel from within the DPhil program. Also the experts can hold lectures in the form of Masterclasses to teach their peers about problems they have encountered.
I co-developed the concept of the Coding Dojo together with our program administrator. I have developed the infra-structure, created and am currently maintaining the webpage as well as the GitHub page. I also assembled the expert board and manage the problem distribution. Within the Coding Dojo I chaired numerous sessions, held multiple masterclasses and written most of the reports which are published on our webpage.
Sessions I have held thus far and wrote reports for include: From sequence to Phylogenetic Tree, Becoming a Terminal Pro, Plotting in Python, Machine Learning for Beginners, Applied Machine Learning in Python, Things I wish I knew before becoming a programmer, A practical Introduction into LaTeXa, Ancestral Sequence Reconstruction
Together with two other doctoral candidates we conceived a neural networks crash course for our fellow D. Phil student. The course ran over 3 separate days with theoretical lectures and programming practicals. I developed and led the recurrent neural networks part of the course.
June 2018 - July 2022
During my doctoral degree I demonstrated on courses on Python, C, html, bash, statisticsand statistical genetics. I also lectured on Python and LaTeX to doctoral students of the years below me.
January 2019 - March 2019
During my 12-week internship in the application team at Oxford Nanopore Technologies I worked on prototyping deep learning algorithms to classify bacterial reads. We achieved a significant boost in accuracy and a speedup of a few orders of magnitude compared to the existing pipeline.
October 2016 - February 2017
During my Master thesis I was part of the research team publishing the first cockroach genome in Blatella germanica and the genome of the termite Cryptotermes secundus. After finishing my MSc I was hired as a research assistant to further work on the publications and analysing the associations between transposable elements and gene family expansions. These efforts resulted in my being co-author of a Nature Ecology and Evolution paper as well as co-first-author of an Experimental Zoology paper. During my time as research assistant I also supervised a Python project of two MSc-students of computer science.
During my Bachelor thesis I was hired as a Student Assistant to help with the supervision of a Python course for BSc, MSc and PhD students focussed on genomic applications.
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