Graduate Program in Computational Science (GPCS)

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Master’s Degree in Computational Science

A Flexible Multidisciplinary Program

Computational Science is a thriving field of study at the interface between computer science, mathematics (and statistics), the natural sciences and engineering (financial included). Practitioners of the art develop mathematical models, construct and optimize numerical algorithms, then deploy the mon increasingly powerful computers, as they address (real-life) scientific problems in fields where quantitative/compute-intensive modeling and simulation are essential to optimal design, predictive analytics, and inference.

The Graduate Program in Computational Sciences (GPCS) at AUB is open to students with backgrounds in computer science, (applied)-mathematics and statistics, natural sciences or engineering, who wish to further their undergraduate experience with computers and computing via intensive (hands-on) study, development and application of state-of-the-art numerical algorithms.

Having completed core courses in the program, a student will then follow a sequence of elective courses, then formulate and tackle problems in fields currently explored at AUB (e.g. machine learning/artificial intelligence/data mining, bioinformatics, biostatistics, operation research, computational (astro)-physics, hydrogeology, structural/ fluid dynamics, networking protocols, cyber-security...etc).

The program prepares the student for a PhD/academic adventure in applied mathematics, computational sciences and related fields, as well as a career in industries or research centers where modeling, simulation, design, and optimization are key.

For more information click here.

Tracks

Admission Requirements

Admission Requirements:

Admission to the master’s program in computational science follows basic AUB regulations. Regular students should be either: 1) holders of a bachelor’s degree in biology, business, computer science, economics, engineering, chemistry, mathematics and physics; have successfully completed the equivalent of CMPS 200, MATH 201, MATH 202, MATH 218 or 219; and have sufficient maturity in discrete mathematics (at the level of MATH/CMPS 211), MATH/CMPS 251, STAT 230(233); or 2) should be holders of a bachelor’s degree, having completed the equivalent of MATH 202, STAT 230 and the FAS core courses requirements for a minor in computational science.

Some candidates may be admitted as prospective students until full completion of the required undergraduate courses. The supplementary courses must be completed within four consecutive, regular semesters.

Graduate assistantships (GFAP) are available for some applicants to the program based on qualifications.

Graduation Requirements

Graduation Requirements:

9 credits consisting of three core courses in advanced numerical methods, optimization and data science, to be selected from the following three baskets respectively:

Advanced Numerical Methods (3 credits)

General

MATH/CMPS 350 Discrete Models for Differential Equations
MATH/STAT 348 Monte Carlo Methods

Discipline Specific

BIOL 370 Bioinformatics
PHYS 310A Computational Physics
MECH 663 Computational fluid dynamics

Optimization (3 credits)

MATH/CMPS 351 Optimization and Nonlinear Problems
ENMG 616 Advanced Optimization Techniques

Data Science (3 credits)

CMPS 392 Machine Learning
EECE 633 Data Mining
EECE 664M/ Introduction to Machine Learning
EECE 667 Pattern Recognition
EECE 693 Neural Networks

12 credits of electives which the student would typically select within one of the program’s approved tracks: Data Analytics, Computational Theory, Bioinformatics, Biostatistics, Computational Biosciences, Computational (Astro)-Physics, Hydrogeology, Continuum Mechanics , Optimization, Operations Research, or Risk Analysis. Alternatively, students can, in coordination with their advisor, and with the approval of the GPCS committee, define a 12-credit track that best suits their background and research interests.
a 9-credit thesis (CMTS 399) in which qualified students demonstrate the ability of constructing, implementing and/or proficiently using computational tools to address problems in their chosen track.

Testimonials

Batoul Sharafeddin - Intern at StellarDevops
"Enrolling in the Computational Sciences program at AUB was one of the best decisions I could make for my career. The challenges that I faced during the program proved to be exceedingly fruitful, as I developed a wide range of skills highly valued among both the industrial and academic workplace. The community was encouraging, helpful, and provided great guidance, which was key for me to succeed in this competitive and result-orientated environment."

Sophie Moufawad - Assistant Professor, Mathematics Department, American University of Beirut (AUB)
"By pursuing this multidisciplinary program, I gained an outstanding knowledge of mathematical modeling, computational and numerical techniques to solve complex problems.Today, as an Assistant Professor in the Mathematics Department at AUB, my research field is Applied Linear Algebra, which is essential to solving many problems in scientific computing."

Dina Kaissi, Computational Science Program Secretary

Email: dk33@aub.edu.lb
Building: Physics (Emile Bustani Hall)/Floor: 1/Room: 102
Ext. 4297

Committee Members

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American University of Beirut

​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Master’s Degree in Computational Science