Assess ability to design a validated, scalable end-to-end workflow that integrates machine-learning-driven de novo peptide design, in-silico screening and prioritization, and high-throughput microfluidic biofilm assays for discovery and iterative optimization of novel antimicrobial peptides active against multi-drug-resistant bacterial biofilms. Test knowledge of dataset curation and augmentation, selection and training of generative and predictive models, sequence-to-activity and toxicity prediction, design-for-manufacturability, microfluidic assay design and quantification of biofilm activity, automation and data pipelines for scale, metrics for validation and reproducibility, iterative design–build–test–learn cycles, and biosafety/regulatory considerations for translational development.