Will Bowers
About Will Bowers
Will Bowers is a Data Scientist with a diverse educational background in biology, bioinformatics, and systems biology. He currently works at Dotmatics, focusing on deep learning methodologies for molecular prediction and generation, while advocating for AI/ML platforms with explainability.
Work at Dotmatics
Will Bowers has been employed at Dotmatics as a Data Scientist since 2020. In this role, he focuses on deep learning methodologies for molecular prediction and generation. Prior to his current position, he worked as a Quality Assurance Analyst at Dotmatics for nine months. His work emphasizes the importance of creating AI and machine learning platforms with explainability, advocating against treating these systems as black boxes.
Education and Expertise
Will Bowers holds multiple degrees in the life sciences and bioinformatics. He earned a Doctor of Philosophy (PhD) from The Institute of Cancer Research, where he studied biomarkers related to tyrosine kinase inhibitor response in soft tissue sarcoma. He also completed a Master of Science (MSc) in Bioinformatics and Theoretical Systems Biology at Imperial College London. His undergraduate education includes a Bachelor of Science (BSc) in Biological Sciences from the University of Leicester, and he has completed A Levels and GCSEs at The Ecclesbourne School.
Background
Will Bowers has a diverse background in research and education. He began his academic journey at The Ecclesbourne School, achieving 10 GCSEs and 4 A Levels. He participated in various research roles, including volunteering as a Caenorhabditis elegans technician and student researcher at the University of Tulsa. His professional experience includes roles at Rolls-Royce as a temporary quantity surveyor and as a personal tutor at Ivy Education.
Achievements
Throughout his career, Will Bowers has engaged in various projects that highlight his commitment to education and public discourse. He participates in podcasting, presentations, and teaching initiatives. He is also active in public speaking, discussing topics such as philosophy, technology, personal improvement, and inclusive sexual health. His advocacy for explainable AI/ML platforms reflects his dedication to transparency in technology.