Senior Research Software Engineer

UK Research and Innovation • 2023 - Present

• Project management and delivery within HNCDI program, from small, quick turnaround proof of concept implementations up to £1m interdisciplinary R&D technology projects.
• Complex stakeholder management across academic, government, and corporate environments.
• Research software deployment in enterprise environments, including Nextflow pipelines, machine learning user interfaces, and LLM serving frameworks for AI applications.
• Grant writing and funding application development for computational research programs, including BBSRC applications up to £200k.
• Grant review board member for BBSRC Facility access funding for bioscience partnerships program (2024 and 2025).
• Team leadership and mentorship of junior research software engineers (5 staff).
• Technical pre‑sales and commercial partnership negotiations, protecting research and stakeholder interests.

Quantitative Systems Pharmacology Modeller

Pharmaceutical CROs • 2020 - 2023

• Developed pipelines for numerical optimization and sensitivity analysis of large ODE models.
• Implemented methods for generating virtual populations from mathematical models.
• Clinical and pharmacokinetic data analysis and visualization.
• Numerical deconvolution methods for pharmaceutical software development.

Data Scientist & Computational Biologist

Science and Technology Facilities Council • 2015 - 2020

• Built bioinformatics pipelines for genomics data annotation and pathway enrichment.
• Developed data pipelines using Apache Airflow and machine learning clustering methods.
• Delivered machine learning models for pharmaceutical industry consortiums.
• Managed industry-academic collaborations for high-performance computing applications.

Research Scientist

Pharmaceutical Industry • 2012 - 2017

• Developed mathematical models of DNA damage repair pathways for cancer drug development.
• Created quantitative systems pharmacology models for respiratory disease applications.
• Supported drug efficacy and dose prediction for clinical trials.
• Mathematical modeling of neutropenia for pharmaceutical consultancy projects.

Microbiologist

Consumer Products & Medical Device Companies • 2000 - 2007

• Conducted microbiology ecology and antimicrobial efficacy studies.
• QC microbiology screening and environmental monitoring of manufacturing facilities.
• Microbial ecology studies supporting consumer product development.
• Specialized in home care, personal care, and wound healing product testing.

PhD Systems Biology

University of Manchester • 2007 - 2011

4 year doctoral training program for systems biology, specialising in using mathematical modelling and simulation to design and test bespoke gene constructs in yeast.

B.Sc (Hons) Microbiology (2:1)

Liverpool John Moore's University • 1996 - 2000

• Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity.
  Gardiner, L. J., Carrieri, A. P., Wilshaw, J., Checkley, S., Pyzer-Knapp, E. O., Krishna, R.
  Nature Scientific Reports (2020), 10(1), 1-8
• Demonstration of the Feasibility of Predicting the Flow of Pharmaceutically Relevant Powders from Particle and Bulk Physical Properties.
  Barjat, H., Checkley, S., Chitu, T., Dawson, N., Farschi, A., Ferreira, A., Gamble, J., Leane, M., Mitchell, A., Morris, C., Pitt, K., Storey, R., Tahir, F., Tobyn, M.
  Journal of Pharmaceutical Innovation (2020), 1-16
• Establishment of intestinal free mucus PK-efficacy relationship for gastrointestinal limited drugs.
  Zhang J. Bendtsen C., Checkley S., Cheng Z.
  ISSX (2017)
• Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738.
  Checkley S. et al.
  Nature Scientific Reports (2015) 5, 13545