1. Mathematical Modeling for Bioinformatics
Minimum of 4 years of experience in using biological data mining and prediction techniques in a cutting edge research environment.
Experience implementing various modeling and prediction techniques, including linear and nonlinear regression, principal component analysis, support vector machines, self-organizing maps, neural networks, set enrichment, Bayesian networks, model-based analysis, and geneset/ pathway/network analysis.
Strong statistics scripting/programming experience.
2. Biological Data Integration
Minimum of 4 years of experience in algorithms and techniques for integration of public and proprietary bioinformatics data in a cutting edge research environment.
Experience with public data resources (e.g., NCBI, Ensembl, UCSC, Broad), relational databases, and methods of data transfer and ontologies (e.g., BioPax, XMLs).
Major school. Cutting edge content area. Learn to teach this subject online and you can write your own ticket.