Software Engineering Intern (MBA or PhD Students)

Thermo Fisher Scientific South San Francisco, CA

About the Job

Summary of Internship

The Machine Learning (ML) Algorithm Development Internship position provides an opportunity for science or engineering students who would like to get hands-on experience working with engineers in a fast-paced R&D environment. The intern will contribute to a research and development project involved with using Machine Learning (ML) and Deep Learning to get (multiplex) quantitative PCR (qPCR) gene expression information from targets that are on the same dye. The position starts in May or June, paid working 40 hours per week through August. An opportunity exists for this position to continue through the academic year on a part-time basis to allow for class schedules.

Essential Functions

  • Prepare and pre-process data for processing with Machine Learning (ML) and/or Deep Learning (DL) Algorithms
  • Prepare and curate data for statistical analysis
  • Evaluate the effect of various ML/DL architectures on the performance and errors (Compare with some initial ideas on how to do this)
  • Analyze data for specific patterns and understand how to express that in terms of the ML/DL architectures investigated and chosen
  • Evaluate algorithm performance
  • Create presentations describing the work (typically every 3 weeks)

Skills and Abilities

  • Strong understanding of, and experience using, ML and DL algorithms.
  • An interest in numerical techniques and signal processing
  • Proficiency with a software language: enough to create tools to manipulate and display data and implement numerical algorithms
  • Ability to work independently and as a member of a cross-functional team
    • Make technical presentations to the cross-functional team
  • Willingness to learn, be mentored, and improve

Qualifications
  • Pursing an MBA or Ph.D. in science or engineering
  • Proficiency with Python, Matlab, and Keras. Strength with TensorFlow is a plus.


To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status.