Integrate and interpret high dimensional data from a variety of high throughput platforms and multidimensional data sources (internal or public) to derive insights and data driven program strategies.

  • Collaborate with colleagues to develop innovative analysis methods and algorithms that solve complex computational research problems.
  • Be accountable for working together to push the boundaries, you blend the best of your talents to unlock innovation.
  • Be certain that your business complies; process, analyze, and interpret high volumes of data for the development and validation of methods.
  • Apply or develop new tools or data mining techniques for integrative analysis and visualization of large data sets.
  • Collaborate with team members in specifying requirements for tools to enhance biomarker discovery.
  • Lead experimental design and provide analysis and critical evaluation of proof of concept/prototype method development activities.
  • Select, test, implement and optimize image processing methods to extract relevant signals from imaging data.
  • Establish that your design complies; rigorous science and careful analysis is critical to the success of everything you aspire to do.
  • Secure that your business prepares report and analysis of results as related to product/process development and improvement.
  • Contribute molecular biology and microscopy expertise to cross disciplinary product development teams.
  • Warrant that your venture complies; as your technology platform develops, you expect to make fundamental changes to your core algorithmic approach.
  • Ensure you outpace; lead the development of new methods and protocols for structural modeling and dynamics.
  • Prioritize and manage multiple experiments in a timely and resource effective manner to enable science based go/no go decision making.
  • Calculate metabolic flux distributions from carbon labeling data and flux balance analysis.
  • Explore alternative experimentation techniques to help internal teams evaluate ideas faster.
  • Collaborate with research and early development leadership to formulate technology evaluation project approaches, plans and deliverables.
  • Bring in datasets from external and internal sources to help develop internal resources for various analytical approaches.


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