PhD in ESS: Data Science Option

The Department of Earth and Space Sciences is partnering with the eScience Institute at the UW to offer a PhD curriculum in Earth and Space Sciences with the Data Science Option (DSO).

The Data Science Option (DSO) is designed to meet a critical educational gap at the intersection of Earth and Space Sciences and Data Science. With the new Data Science Option, the ESS graduates will be equipped to tackle modern ESS challenges using large datasets, machine learning, statistical inference, and visualization techniques. The ESS DSO provides students with a foundation in the field of data science, builds critical knowledge and skills to apply to a variety of modern data analysis techniques, and tools to advance and accelerate ESS research and applications.

The ESS DSO is designed for students with little background in data science, computer science, or coding.

Overview of ESS DSO Requirements

In addition to the requirements for the ESS Research Program courses, Data Science Option students additionally take:

  • 11 credits from the Standard Data Science Option list below. At least 3 out of 4 courses from the thematic fields
    • Software Development for Data Science: CSE583, ME574, CHEM 546, AMATH 583
    • Statistical and Machine Learning: ATM  552, FISH 546, FISH 560, SEFS 502; CEE 465, CET 521-IND E 546, CSE/STAT 416, CSE 546, CSE 599, ME/EE 578, ME 599; AMATH 515, AMATH 563, AMATH 582, STAT 435, STAT 509, STAT 512-513, STAT 535
    • Numerical Modeling, Data Management, Data Visualization: AMATH 581, ATM 559, ATM 581, ATM 582, FISH 454, FISH 458, FISH 554, FISH 556, FISH 559, OCEAN 502, SEFS 502, SEFS 540, SEFS 557; CSE 414, CSE 412, CSE 512, CSE 544, HCDE 411/511;
    • Department-Specific Courses related to Data Science: ESS 420, ESS 469/569, ESS 521, ESS 522, ESS 523, ESS 524, ESS 529
  • 2 credits CHEM E 599 (Topics in Data Science)

eScience Community Seminar

In addition to the course requirements listed above, students must also participate in 2 quarters of the 1-credit eScience Community Seminar. This is an informal environment for presentations and discussions. Topics span science, methods, and technology across the mission of the eScience Institute.

eScience Community Seminar

Rationale and Learning Outcomes

Research in the Earth & Space Sciences is rapidly expanding it use of enormous, complex and heterogeneous data sets, also known as “big data”. Especially in the disciplines of geophysics, glaciology, planetary remote sensing, climate modelling, igneous, metamorphic, sedimentary and tectonic processes, students require new data science skills that would be provided by the ESS-DSO.

The choice of learning outcomes that will benefit the students who pursue the Data Science Option include:

  • Ability to manipulate large, heterogeneous and complex data sets
  • Develop mathematical and computational skills to analyze and interpret big data obtained from natural systems
  • Become proficient with techniques to visualize big data and communicate its implications to the Earth Sciences
  • Understand the use of machine learning and predictive analytics to analyze complex data from natural systems

Student Eligibility

Eligible students for the DSO include all full-time students in the ESS PhD program who are in good standing. Interested students will contact the ESS Graduate Program Coordinator and declare interest in pursuing the DSO. The student’s primary research advisor must approve the application.

Back to Top