Research Assistant
• Contributed to the development of an innovative, non-invasive and rapid silicosis diagnosis method, utilizing mass spectrometry and interpretable machine learning algorithms• Promoted the study to interested research groups and philanthropists by presenting study results at meetings and networking at conferences• Secured ethics approval by drafting and submitting essential documentation for the study, involving up to 600 participants• Developed the patient database and coordinated data capture activities• Performed chart reviews and consented over 400 study participants from a private clinic and university• Assisted study participants with questionnaire completion, breath sample collection and lung function testing• Maintained study health by providing weekly study updates to the Principal Investigator, and quarterly progress and budget reports to the granting body