Louise Bowler
Senior Research Software Engineer at King's College London
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolLouise Bowler is a Senior Research Software Engineer with 12 years of interdisciplinary experience spanning physics, computer science, biology and mathematical modelling, and a DPhil in Computational Biology from the University of Oxford. She builds robust, production-ready research software and data platforms—recently delivering Python-driven dashboards and analytical tools for the UK Ministry of Justice and developing reproducible research infrastructure at the Alan Turing Institute. Comfortable in both research and operational environments, she combines scientific rigour with practical DevOps skills (Docker, Kubernetes, AWS, Terraform) to move analytic prototypes into reliable services. Louise is also committed to community-building and reproducibility best practices, having contributed to The Turing Way and led training and upskilling efforts for colleagues new to Python. Notably, her work connects mechanistic computational modelling (e.g., cardiac simulations) with scalable data engineering, giving her a rare ability to translate complex scientific questions into maintainable software.
12 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science (Computational Biology), Doctor of Philosophy - PhD Computer Science (Computational Biology) at University of OxfordMSci Physics, MSci Physics at Imperial College London
Github Skills (53)
data-science10
classification10
machine-learning10
electrophysiology10
reporter10
hpc-applications10
lstm10
cloud-platform10
computational-biology10
science10
sequential10
pytorch9
signature9
synthetic9
deep-learning9
Programming languages (7)
Github contributions (5)
alan-turing-institute/bocpdms
Jul 2018 - Nov 2018
Contributions:55 commits, 9 PRs, 15 pushes in 3 months
kochkinaelena/branchLSTM
Jun 2018 - May 2019
branchLSTM model from Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM
Contributions:55 commits, 7 PRs, 23 pushes in 11 months
pytorchdeep-learningapproachlstmmachine-learning
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