Summary
Patrick Bryant is an Assistant Professor and computational biologist with a decade of experience applying deep learning and statistical models to structural biology and biomolecular interaction design. He holds a PhD in Bioinformatics and Deep Learning and has advanced from PhD work at SciLifeLab to postdoctoral research in Berlin and a faculty role at Stockholm University, where he focuses on AI-driven structure prediction and design. His background spans hands-on lab techniques (NGS, HPLC, GC-MS) and production bioinformatics (Python, Nextflow, Unix), enabling him to bridge experimental and computational workflows. Patrick is known for tackling hard problems in structural biology by translating complex data into usable applications and methodologies. Colleagues describe him as a dedicated scientist who pairs rigorous research with practical engineering instincts, often contributing code and reproducible pipelines on GitHub.
10 years of coding experience
1 year of employment as a software developer
MSc in Engineering Biotechnology, MSc in Engineering Biotechnology at KTH Royal Institute of Technology