Computational Sciences and Engineering

The Bachelor of Science in Computational Sciences and Engineering at Koç University is a comprehensive undergraduate program designed to equip students with a strong foundation in computer science, applied mathematics, and engineering principles. This interdisciplinary program aims to prepare graduates for the rapidly evolving fields of data science, software engineering, and computational modeling by integrating theoretical knowledge with practical problem-solving skills. Students will engage in rigorous coursework covering algorithms, programming languages, data structures, numerical methods, and advanced topics like machine learning, artificial intelligence, and high-performance computing. The curriculum emphasizes experiential learning through laboratory exercises, projects, internships, and research opportunities, fostering critical thinking and innovation. Additionally, students have access to state-of-the-art facilities and are encouraged to participate in collaborative projects with industry partners and research centers, gaining hands-on experience that bridges academic concepts with real-world applications. The program also emphasizes ethical considerations and societal impacts of computational technologies to develop responsible practitioners. Graduates of this program are prepared for careers in software development, data analysis, research, and academia, or for pursuing advanced studies such as master's and doctoral programs. With a strong emphasis on interdisciplinary education, the Computational Sciences and Engineering program at Koç University nurtures versatile professionals capable of tackling complex computational challenges across various sectors including technology, finance, healthcare, and engineering industries.

The Computational Sciences and Engineering program at Koç University offers a comprehensive curriculum designed to equip students with advanced knowledge and practical skills in computational methods, data analysis, and scientific computing. The program aims to prepare graduates for both academic research and industry roles that require expertise in computational problem-solving across various engineering and scientific disciplines. Students will engage in coursework that covers numerical analysis, algorithms, high-performance computing, data structures, machine learning, and data-driven decision making. The curriculum emphasizes developing strong foundational knowledge while promoting innovation through project-based learning, research opportunities, and collaborations with industry partners.

In the thesis track, students undertake an in-depth research project under the supervision of faculty members, allowing them to explore specialized topics such as computational modeling, scientific simulation, or big data analytics in detail. The non-thesis track focuses on coursework and practical applications, providing students with the tools to address real-world computational challenges effectively. Both tracks are designed to foster critical thinking, problem-solving abilities, and technical proficiency essential for careers in academia, research institutions, or high-tech industries. The program benefits from Koç University’s state-of-the-art laboratories and computational facilities, providing an excellent environment for hands-on learning and experimentation.

Graduates of the Computational Sciences and Engineering program will be well-positioned to pursue careers in sectors such as software development, data science, engineering analysis, scientific research, and technological innovation. They will also have the option to continue their academic journey through doctoral studies. The program’s interdisciplinary approach, combining computer science, engineering principles, and scientific inquiry, prepares students to tackle complex computational problems and contribute to technological advancements in various domains.

Program requirements for the MSc in Computational Sciences and Engineering (Thesis and Non-Thesis Programs) at Koç University include the completion of coursework totaling at least 30 credits, which encompass core courses in computational methods, scientific computing, data analysis, and programming, as well as electives allowing specialization in areas such as machine learning, high-performance computing, and applied mathematics. Students are expected to maintain a minimum GPA as specified by the university, typically around 2.75 on a 4.0 scale, to ensure satisfactory academic progress. For the thesis track, candidates must formulate and defend a research proposal, followed by the successful completion of a thesis project under the supervision of a faculty advisor, culminating in an oral defense and submission of a written thesis document. Non-thesis students are required to complete additional coursework and a comprehensive final examination to demonstrate proficiency in key areas of computational sciences. Both tracks require students to pass comprehensive qualifying exams that assess core knowledge in computational mathematics, algorithms, and computer programming. Additionally, students seeking graduation must fulfill language proficiency requirements, often demonstrated through TOEFL or IELTS scores, unless waived by prior demonstrated English proficiency. The program encourages active participation in seminars, workshops, and research labs to foster practical skills and research experience. International students must comply with visa regulations and maintain full-time enrollment status. Administrative requirements include timely registration each semester, submission of academic progress reports, and adherence to university academic integrity policies. As part of the program, students also have opportunities to collaborate on interdisciplinary projects and present their research findings at national and international conferences. Overall, the program aims to equip graduates with theoretical knowledge and practical skills necessary for careers in academia, industry, and research organizations, emphasizing innovation and interdisciplinary approaches in computational sciences.

Financial Aid
The students who get the KU full-scholarship, will be supported with one of thepackages below; For MS Students (Thesis Programs):
* Students admitted with a BS/BA degree will have the folowfing offer: * Tuition waiver (33,500 TL/year) plus 1,150 TL monthly stipend, housing.



For PhD Students:
* Students admitted with a BS/BA degree will have the following offer: * Tuition waiver (33,500 TL/year) plus 1,150 TL monthly stipend, housing. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier.


* Students admitted with a MS/MA degree will have the following offer: * Tuition waiver (33,500 TL/year) plus 1, 400 TL monthly stipend. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier



Additional Benefits:

* All students receive a laptop computer and private health insurance.
* Students with successful standing receive travel funds to attend scientific conferences and meetings.
* PhD students with higher GPA degrees may be offered super scholarship up to 2,500 TL .
* Students who receive their stipend from other sources (like TÜBITAK scholarships or externally funded research grants and projects) are eligible for the following benefits provided by the university:

* Research Award: 1,300 TL
* Free Housing: This includes all costs except telephone expenses.
* Research Award for PhD students: 2,000 TL/year after they pass the qualifier.

The Master’s program in Computational Sciences and Engineering at Koç University is designed to provide students with a comprehensive understanding of computational methods, algorithms, and their applications across various scientific and engineering disciplines. This program aims to equip students with the essential skills necessary for research, development, and innovation in fields that rely heavily on computational techniques, such as data science, machine learning, simulations, and modeling. The curriculum is carefully structured to blend theoretical foundations with practical applications, ensuring graduates are proficient in programming, numerical methods, and problem-solving strategies relevant to real-world challenges.

Students have the opportunity to choose between a thesis and a non-thesis track, allowing them to tailor their educational experience according to their career goals. The thesis option emphasizes original research, requiring students to identify a research problem, conduct experiments or simulations, and produce a substantial thesis document. This pathway is suitable for students intending to pursue doctoral studies or careers in research environments. The non-thesis track focuses more on coursework and practical training, preparing students for roles in industry where applied computational skills are in high demand.

Koç University emphasizes interdisciplinary collaboration, and students often have access to cutting-edge laboratories and computational resources. Faculty members are experienced researchers and practitioners in areas such as scientific computing, applied mathematics, machine learning, artificial intelligence, and data analysis. The program’s structure includes core courses in programming languages, algorithms, applied mathematics, and specialized electives catering to areas like deep learning, data mining, computational physics, and bioinformatics.

Moreover, the program encourages students to participate in seminars, workshops, and industry-sponsored projects, facilitating connections with academia and industry partners. Graduates of this program are well-positioned to work in academia, research institutions, and a broad spectrum of industries including technology, finance, healthcare, and manufacturing. The program’s rigorous academic approach and strong industry links ensure that students gain both theoretical knowledge and practical experience vital for their professional growth. Overall, the Computational Sciences and Engineering program at Koç University prepares students to be innovative problem-solvers and leaders in the rapidly evolving landscape of computational technology.