The COS program aims at providing highly interdisciplinary training to educate researchers to use advanced computational and data methodologies to solve complex scientific and engineering problems. It provides a unified approach to modeling, high-performance computing and data science, and artificial intelligence-based approaches. Through modeling, simulation, machine learning, and the study of specific phenomena, the program delivers cross-disciplinary knowledge but also domain-specific depth in fields like computational fundamental physics, climate modeling, computational fluid dynamics, computational biology, materials science, computational economics, and digital cultural heritage. The program provides the necessary educational setting where excellence in education and research is fostered through interdisciplinary collaboration.
Learning Outcomes
The program produces researchers who will be leaders in Computational Science with specialization in important fields that require High-Performance Computing and Artificial Intelligence. They learn to apply computational modeling and simulation, develop numerical algorithms, understand high-performance computer architectures, use data, optimization, error quantification, and statistical analysis to provide insights to the world’s most complex systems, such as Earth Systems Science, Fundamental properties of matter, Biotechnology, Genomics, and Drug Design, Digital Cultural Heritage and Economic Science.
General Admissions Information and Requirements
The doctoral programs are highly selective and are designed for research-oriented students aspiring to become leaders in their respective fields of study. Students who are admitted to the program are immersed in a rigorous international research environment that will require a full-time commitment for the duration of the program.
To be considered for admission to a Ph.D. program, a student must have the following:
1. A Master's degree from a recognized accredited institution, with a strong academic record in a major field of study and background relevant to the proposed graduate-level studies.
2. Proof of English language proficiency
If your first language is not English, you must provide recent evidence that your spoken and written command of the English language is adequate for the program to which you are applying. Proof of English language proficiency may be demonstrated by submitting one of the following certificates (or equivalent as deemed by the Admissions Committee).
IELTS Academic Version: at least 6.5 (taken within the past 2 years)
TOEFL Internet-based Test: at least 79 (taken within the past 2 years)
GCSE/IGCSE: Grade C or above (preferably with speaking)
IELTS or TOEFL is preferred.
The English Language proficiency test requirement may be waived if you have/will graduate from a higher education institution in which English is the medium of instruction and communication or if you have a minimum of eighteen months of work experience in a country that CyI considers to be “majority English speaking”, no more than two years prior to the proposed date of registration.
3. Due to the nature of the Ph.D. program, strong computational skills are required.
Review and Selection Process for Doctoral Program
The Admissions Committee reviews applications and makes its decision on the basis of the student’s academic merit and the match between the Institute’s research activities and the student’s research interests, i.e. Cyi’s capacity to support the students’ Master’s research in terms of facilities, infrastructure, and supervision.
Candidates may be asked for a personal interview. If students are abroad, they may be interviewed through a video conference call.
Criteria and processes for the recognition of previous studies and credit transfers
All CyI’s Ph.D. and Master’s degree programs adhere to the Bologna Process second and third cycle degrees and use the ECTS credit system, ensuring that its degrees are recognized around the world. The ECTS system utilizes a credit concept to compare courses by workload for a typical student. At the CyI, one (1) ECTS is calculated as being the equivalent of 25 hours of workload, both contact and distance learning hours.
Previous degrees are recognized if students have attended an institution(s) that is/are accredited by the appropriate competent body in the country in which it operates. This is stated clearly in the admissions section of our website.
Recognition of ECTS credits
In the cases where a student wishes to transfer ECTS credits acquired previously towards another degree or outside any degree, the Mentor/Dissertation Advisory Committee of the student will assess the relevance of the specific credits in terms of learning objectives and a decision will be made regarding the transfer. The decision will have to be approved by the Academic Committee. A quota of up to 1/3 of the program requirements can be credited from transfer credits if the Academic Committee approves.
