Josh is formally trained in Mathematics, Computer Science and Biology, with extensive experience analyzing High Throughput sequencing datasets. He particularly focuses on the association of phenotypic measures with underlying sequencing features through the application of Machine Learning and Statistical modeling.
- Application of Statisical Modeling and Machine Learning to Biological Questions
- Analysis of High-Throughput Sequencing Data, including:
- DNA Variant Detection
- Development of Analytical Techniques for Novel Experimental Designs
- Analysis of Cytometric Data, including:
- Quantification of Cell Populations
- Analysis of Intrinsic and Extrinsic Noise
University of Minnesota, Minneapolis, Minnesota:
- PhD, Biomedical Informatics and Computational Biology
- BS, Math in Computer Applications
- BS, Genetics
General educational emphasis on the fields of Mathematics, Computer Science, Molecular Biology, and Genetics.