Antibiotic Resistance Data Analysis

I have a set of microbiology results and need an experienced medical laboratory scientist or bioinformatician to interpret the data with a focus on antibiotic resistance patterns. The raw files include susceptibility panels and MIC values; I’m looking for clear insights that can guide both clinical decision-making and future research.

Key objectives
• Parse and clean the data, flagging any inconsistencies.
• Quantitatively assess resistance trends across isolates, drug classes, and time points.
• Summarize findings in a concise, publication-ready report that meets common laboratory QA standards (CLSI/EUCAST).
• Provide actionable tables, graphs, and brief commentary suitable for inclusion in a scientific manuscript or internal QA review.

Preferred skill set
• Strong background in clinical microbiology and antimicrobial stewardship.
• Proficiency with R, Python, or comparable statistical tools for biomedical data interpretation.
• Familiarity with laboratory quality assurance frameworks.

Deliverables
1. Annotated analysis script or notebook.
2. Cleaned dataset with metadata.
3. PDF/Word report outlining methodology, results, and conclusions.
4. High-resolution figures (PNG or TIFF) illustrating resistance profiles.

If you have handled similar datasets and can deliver precise, standards-compliant interpretations, I’d like to collaborate. Please share a brief outline of your approach and a relevant sample of prior work.