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.

More Uses of the Computational Biology Toolkit:

  • 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.
  • Govern: development of your core algorithm is guided by performance benchmarking on real and simulated data (to forecast future performance and what if scenarios).
  • Lead experimental design and provide analysis and critical evaluation of proof of concept/prototype method development activities.
  • Devise: form partnerships with cross functional teams in adjacent research domains to improve optimization of complex workflows.
  • Manage: in Computational Biology, bioinformatics, biostatistics, computer science, or similar discipline.
  • Select, test, implement and optimize image processing methods to extract relevant signals from imaging data.
  • Develop: on an on going basis, communicate feedback and ideas for new tools, improvement of existing tools, and general prioritization of computational needs.
  • Initiate: when you come to work, you strive to achieve excellence and pursue your goals with a sense of urgency.
  • Establish that your design complies; rigorous science and careful analysis is critical to the success of everything you aspire to do.
  • Organize: development of a reproducible performance benchmarking framework to track current and predicted quantitative accuracy, sensitivity, and precision.
  • Control: location and schedule is subject to change at any time for any reason based on business needs.
  • Pilot: in computer science, software engineering, bioinformatics, systems biology, Computational Biology, or a related field.
  • Secure that your business prepares report and analysis of results as related to product/process development and improvement.
  • Steer: design statistical and machine learning models to analyze large scale collections of sequence data.
  • Systematize: work closely with data science, platform, and biology teams to create and execute appropriate data analysis plans.
  • 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.
  • Systematize: how to handle and efficiently analyze data with increasing complexity is quickly becoming the next bottleneck.
  • 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.
  • Formulate: accuracy through more sophisticated modeling of biophysical phenomena and machine learning approaches where appropriate (as guided by data).
  • Bring in datasets from external and internal sources to help develop internal resources for various analytical approaches.
  • Direct: in bioinformatics, Computational Biology, biostatistics, biology or a related discipline.

 

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