The M.S. CompGeo track is offered through the Institue for Computational Mathematics and Engineering. For more information about the requirements and admissions process please see the ICME website.
Students are required to take 45 units of coursework, and research credits to earn an M.S. in CompGeo. The coursework follows the requirements of the traditional ICME M.S. degree with additional restrictions placed on the general and focused electives. As defined in the general Graduate Student Requirements students have to maintain a grade point average (GPA) of 3.0 or better and must be taken at the 200 level or higher. In order to continue on to the Ph.D. in ICME M.S. students have to maintain at a GPA of at least 3.5.
Requirement 1: Foundational
Students must demonstrate foundational knowledge in the field by completing four courses among the following 6 core courses (notice that CME 298 is an accepted alternative to CME 308)
Courses in this area must be taken for letter grades. Deviations from the core curriculum must be justified in writing and approved by the student’s ICME adviser and the chair of the ICME curriculum committee. Courses that are waived may not be counted towards the master’s degree.
Requirement 2: Programming
3 units of programming course work demonstrating programming proficiency. All graduate students in the program are required to complete programming course at the level of CME 212 or higher.
Requirement 3: Breadth Electives
The M.S. CompGeo track requires 18 units of course work in the Geosciences (3 units can be applied from a non-computationally focused course). Courses are currently offered but are not limited to the following specific areas of the School of Earth, Energy & Environmental Sciences:
- Reservoir Simulation
- Geophysical Imaging
The Earth Science courses, offered in EESS, ERE, GES, and Geophysics is selected based on the area of the student's interest and their research/thesis work, along with the advice and consent of the student's adviser. Students are encouraged to choose a range of courses in order to guarantee breadth of knowledge in Earth Sciences. A maximum of one non-computationally-oriented course can be counted towards the master’s degree requirements. A list of courses that fulfill this requirements is available at Course Listings
Requirement 4: Practical Component (Integrative Research in Computational Geoscience)
9 units of focused research in computational geoscience. Students are required to either complete a Research Project or an Internship as described below.
Students who plan to apply to the Ph.D. program need to take 9 units of research. Students will work with the CompGeo program director to find an appropriate advisor and research topic and then enroll in EARTHSCI 400:Directed Research (or a similar School of Earth, Energy & Environmental Sciences research course). The successful outcome of a Research Project can be:
- an oral presentation at an international meeting requiring an extended abstract
- a publication submission in a peer reviewed journal.
- a written report
As an alternative to the Research Project students have the option of an internship which is recommended for those students interested in a terminal degree. The individual student is responsible for securing and organizing the internship and is required to obtain a faculty advisor and submit a written report on the internship project. Credit for the internship will be obtained through EARTHSCI 401: Curricular Practical Training (1 unit) and in this case only 8 units of research are required.
Requirement 5: Seminar
3 units of ICME graduate seminars or other approved seminars. Additional seminar units may not be counted towards the 45-unit requirement.One of the required seminars for CompGeo must be EARTHSCI 310Computational Geosciences Seminar (1 unit).
Note: Fundamental courses in mathematics and computing may be needed as prerequisites for other courses in the program. Check the prerequisites of each required course. Preparatory courses include such subjects as: calculus, linear algebra and differential calculus of several variables, integral calculus of several variables, ODEs with linear algebra, linear algebra and matrix theory, vector calculus for engineers, linear algebra and PDEs for engineers, introduction to scientific computing, linear algebra with application to engineering computations, PDEs in engineering, Computer Programming in C++ for Earth Scientists and Engineers, Introduction to Large-Scale Computing in Engineering, numerical linear algebra, programming methodology, programming abstractions, machine learning, introduction to optimization, theory of probability, and data mining and analysis.