Career Profile
Originally a bench scientist in the field of molecular biology, I have developed skills to answer difficult questions of disease and biomarker discovery through computer code. My career has co-evolved with the challenges of mass spectrometry based and clinical data analysis. My technical and leadership skills are transferable to answering any data challenge in most disciplines. I believe in strongly applied fundamentals of code engineering (testing, Agile, clear code).
I am currently seeking a position as a Data Scientist, Bioinformatics Scientist or Computational Scientist at the mid to senior level. I am willing to relocate!
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Work Experience
Performing data analysis of complex clinical cohorts. Custom computational pipeline development. Network analysis for human metabolic pathways.
Lead developer for computational framework to assemble sample specific databases using metabolomics mass spectrometry data. Biomarker discovery using informatics workflows for elucidating the varied treatment response of asthmatic children using metabolomics. Lectures in UCD Comp. Bio. Program core classes and metabolomics workshops.
Lead developer for computational framework to assemble sample specific databases. Lab transfered to UCD for continuing work.
Analyzed trypsin digestion efficiencies through mass spectrometry data. Developed Java program to analyze NIST MS data.
Body of dissertation work completed profiling the renal response to metabolomic acidosis using mass spectrometry based proteomics. Teached biochemistry laboratories to undergraduates.
ELISA development, serum biomarker profiling and flea insectiside target identification and expression for molceular and biological contact assay.
DNA transcription factor footprinting using manual sequencing techniques. TFIIa affinity purification from Acanthamoeba.
Awards
Teaching Experience
Lecture in Multiple Sequence Alignment, computational aspects.
Lectures in proteome and metabolome informatics.
Lectures and hands-on computer laboratories in 'R for Metabolomics Data Analysis', 'WebTools for Metabolomics Data' and 'Introduction to Statistics'.
Basic hands-on techniques in molecular biology and protein biochemistry.
Basic hands-on techniques in cell biology.