Applied Mathematics and Computational Science MS Program

Program Mission: 
The mission of the Master’s Program in Applied Mathematics and Computational Science is to prepare graduates to become skilled researchers, innovators, and problem-solvers who can apply advanced mathematical modeling, computational techniques, and data-driven methods to contribute to the broader community through addressing complex real-world challenges

Program Goals: 
Graduates of the Master’s Program in Applied Mathematics and Computational Science will be able to: 
Enable students to apply advanced mathematical and computational methods to real-world problems. 
G2: Contribute to the broader community by Integrating theory with practice to design effective solutions
G3: Contribute to research, innovation, and technological advancement. 

Program Learning Outcomes (PLOs) 
 

Knowledge and Understanding: 
K1: Demonstrate in-depth knowledge of applied mathematics, numerical analysis, and computational science. 
K2: Explain mathematical models and computational methods for analyzing scientific and engineering problems. 
K3 Critically evaluate research literature and emerging trends in applied mathematics and computational science. 

Skills:  
S1: Formulate complex real-world problems as mathematical models. 
S2: Design, implement, and analyze efficient numerical algorithms and computational solutions. 
S3: Use modern programming languages, software tools, and high-performance computing environments effectively. 
S4: Communicate mathematical and computational results clearly in written, oral, and visual formats. 

Values, Autonomy, and Responsibility:  
V1: Conduct research and problem-solving with integrity and adherence to professional ethics. 
V2: Take responsibility for independent learning and continuous professional development. 
V3: Apply mathematical and computational expertise to contribute to societal and technological advancement. 
V4: Demonstrate initiative, creativity, and leadership in professional or research settings.

 

 

MS Course Requirements

MS students must complete the following requirements:

  • Core Courses (12-15 credits)
  • Elective Courses (9-12 credits)
  • Research/Capstone (12 credits)
  • Graduate Seminar (non-credit)
  • Winter Enrichment Program (WE 100)

All AMCS students must earn at least 24 credits from Core/Elective Courses, not including credits from AMCS 201, AMCS 202, AMCS 206, and STAT 210.These are graded on letter scale but do not count towards the requirements. Core and Elective Courses must be technical courses and cannot be substituted with Research or Internship to fulfill degree requirements.

Core Courses (12-15 credits)

Core Courses provide students with the background needed to establish a solid foundation in the program area. Students must complete between 12-15 credits (4- 5 Core Courses) dependent on their track and be aware that Core Courses may be offered only once per academic year.

Applied Mathematics (AM) Track

Students on the Applied Mathematics (AM) Track must take five Core Courses (15 credits) from the following list:

AMCS 231Applied Partial Differential Equations I

3

AMCS 235Real Analysis

3

AMCS 251Numerical Linear Algebra

3

AMCS 252Numerical Analysis of Differential Equations

3

AMCS 241Stochastic Processes

3

Or

STAT 220Probability and Statistics

3

Students must choose between AMCS 241 and STAT 220.

Computational Science and Engineering (CSE) Track

Students on the Computational Science and Engineering (CSE) Track must take four Core Courses (12 credits). Two courses (6 credits) should be taken from the following list:

AMCS 231Applied Partial Differential Equations I

3

AMCS 251Numerical Linear Algebra

3

AMCS 252Numerical Analysis of Differential Equations

3

AMCS 241Stochastic Processes

3

Or

STAT 220Probability and Statistics

3

Only one of AMCS 241 or STAT 220 may be counted toward this requirement. Additionally, students enrolled in the CSE track are required to take two courses, totaling 6 credits, from the Computer Science (CS) Program Core Course List. Three of these credits can be earned from the course CS201.

Data Science (DS) Track

Students on the Data Science (DS) Track must take four Core Courses (12 credits) from the following list:

AMCS 211Numerical Optimization

3

AMCS 215Mathematical Foundations of Machine Learning

3

AMCS 251Numerical Linear Algebra

3

AMCS 241Stochastic Processes

3

Or

STAT 220Probability and Statistics

3

Students must choose between AMCS 241 or STAT 220Core courses can be replaced by 300-level courses in the same research area if the student has previously taken a similar course. This substitution must be approved both by the Academic Advisor and by the AMCS Curriculum Committee. 

Elective Courses (9-12 credits)

Elective Courses allow students to tailor their educational experience to meet individual research and educational objectives with the permission of the Academic Advisor.

Applied Mathematics (AM) Track

Students in the AM Track must take three Elective Courses (9 credits). Courses can be taken from any KAUST Program. Those taken outside the AMCS program must be approved by the Academic Advisor. Refer to the KAUST Course Catalogue for choices.

Computational Science and Engineering (CSE) Track

Students in the CSE track must take a total of four Elective Courses (12 credits) as per the following requirements:

  • Two courses (6 credits) in Applications of Modeling. Eligible courses can be found here. This list is not exclusive. At least one modeling course should be from outside the AMCS Program. The choice of modeling courses must be approved both by the Academic Advisor and the Program Chair.
  • Two AMCS courses (6 credits)

Data Science (DS) Track

Students in the DS track must take four Elective Courses (12 credits).The choice of courses must include the following:

  • One AMCS Course (3 credits)
  • Two courses (6 credits) from the Data Science course list maintained by the AMCS Curriculum Committee.
  • Any other course from KAUST Programs (3 credits) as approved by the advisor

Graduate Seminar (non-credit)

Students must register for AMCS 398 and receive a Satisfactory grade for two Semesters during their MS.

Winter Enrichment Program (non-credit)

All students must complete the Winter Enrichment Program (WE 100) for credit at least once during their studies at KAUST. Students who have previously completed WEP will be exempt from this requirement in their future studies. 

MS Thesis

Students planning to pursue the Thesis option must complete a minimum of 12 credits of Thesis Research (AMCS 297).

For more details on the Thesis Application, Thesis Committee Formation, Thesis Defense Results, Thesis Document and  Thesis Archiving please check the policy page.

MS Non-Thesis

Students wishing to pursue the non-thesis option must complete a total of 12 capstone credits, with 6 credits of directed research (AMCS 299). Students must complete the 6 remaining credits through one of the options listed below:

  • Internship: Summer internship (AMCS 295) – students can only take one internship
  • Any 200/300-level courses from any degree program at KAUST.