PhD in Computational Sciences and Statistics 36 months PHD Program By Al-Farabi Kazakh National University |Top Universities
Subject Ranking

# 601-650QS Subject Rankings

Program Duration

36 monthsProgram duration

Main Subject Area

Computer Science and Information SystemsMain Subject Area

Program overview

Main Subject

Computer Science and Information Systems

Degree

PhD

Study Level

PHD

Study Mode

On Campus

The program is aimed at training high qualified scientific, pedagogical personnel, competitive in the domestic and international labor market in accordance with their needs and the prospects for the development of the country and the region. The educational program is focused on the formation of students' deep knowledge in the field of computational sciences and statistics, calculation methods, analysis of the convergence of schemes, the use of statistical methods for data analysis and forecasting based on mathematical calculations, the development of skills in the implementation of scientific research and pedagogical activities at the university and research institutes. The following areas of training are provided: - Computational methods for solving problems for partial differential equations; - Analysis of the convergence of approximation schemes for the numerical solution of problems of mathematical physics; - Construction and use of various types of computational grids with adaptation; - Formulation of differential equations based on hypotheses for setting model problems; - Using the methods of mathematical statistics on real data to select the parameters of computational models; - Predicting the development of the simulated process using numerical experiments; - Development and use of high-performance computing algorithms for the numerical solution of problems in mathematical physics; - Self-development, scientific thinking, critical analysis, allowing you to work in new research areas like quantum computing. - Computational forecasting of problems in physics, chemistry, biology, financial processes, geology, kinetics.
ON1. Conduct scientific research and obtain new fundamental and applied results, critically analyze and evaluate the results obtained, formulate sound conclusions even in conditions of incomplete or limited information;
ON2. Write scientific articles in foreign and domestic journals and inform the wide scientific community of advanced topics and research results at international and national conferences, seminars and workshops, critically assessing their significance;
ON3. Write independent scientific projects and applications, setting a theoretical or practical computational problem or a solution method that is relevant to society, implement and correct, if necessary, the process of independent scientific research;
ON4. Determine the direction and intensity of their professional development in the chosen scientific field, be able to work in a team and contribute to the development of the team and society as a whole.
ON5. Conduct research in the field of methodology of computational experiments based on approximating differential equations by methods of finite differences, volumes and / or elements.
ON6. Conduct a fundamental analysis of computational methods and difference schemes for convergence and correctness, including in the case of high-performance algorithms.Create and use correct structured, curvilinear, unstructured computational grids in computational problems;
ON7. To formulate the task of statistical analysis and evaluation in the chosen subject area, to select and apply statistical tools and software. To master new methods of applied and mathematical statistics for their use in analytical work:
ON8. Develop parallel computing algorithms for engineering problems and implement them in high-performance systems, develop quantum computing algorithms.
ON9. Use the methods of mathematical statistics on real data for the selection of parameters, adaptation and testing of computing systems based on real experiments
ON10.Use data mining methods based on deep learning, reinforcement learning to adapt the computational algorithm to effectively predict results

Program overview

Main Subject

Computer Science and Information Systems

Degree

PhD

Study Level

PHD

Study Mode

On Campus

The program is aimed at training high qualified scientific, pedagogical personnel, competitive in the domestic and international labor market in accordance with their needs and the prospects for the development of the country and the region. The educational program is focused on the formation of students' deep knowledge in the field of computational sciences and statistics, calculation methods, analysis of the convergence of schemes, the use of statistical methods for data analysis and forecasting based on mathematical calculations, the development of skills in the implementation of scientific research and pedagogical activities at the university and research institutes. The following areas of training are provided: - Computational methods for solving problems for partial differential equations; - Analysis of the convergence of approximation schemes for the numerical solution of problems of mathematical physics; - Construction and use of various types of computational grids with adaptation; - Formulation of differential equations based on hypotheses for setting model problems; - Using the methods of mathematical statistics on real data to select the parameters of computational models; - Predicting the development of the simulated process using numerical experiments; - Development and use of high-performance computing algorithms for the numerical solution of problems in mathematical physics; - Self-development, scientific thinking, critical analysis, allowing you to work in new research areas like quantum computing. - Computational forecasting of problems in physics, chemistry, biology, financial processes, geology, kinetics.
ON1. Conduct scientific research and obtain new fundamental and applied results, critically analyze and evaluate the results obtained, formulate sound conclusions even in conditions of incomplete or limited information;
ON2. Write scientific articles in foreign and domestic journals and inform the wide scientific community of advanced topics and research results at international and national conferences, seminars and workshops, critically assessing their significance;
ON3. Write independent scientific projects and applications, setting a theoretical or practical computational problem or a solution method that is relevant to society, implement and correct, if necessary, the process of independent scientific research;
ON4. Determine the direction and intensity of their professional development in the chosen scientific field, be able to work in a team and contribute to the development of the team and society as a whole.
ON5. Conduct research in the field of methodology of computational experiments based on approximating differential equations by methods of finite differences, volumes and / or elements.
ON6. Conduct a fundamental analysis of computational methods and difference schemes for convergence and correctness, including in the case of high-performance algorithms.Create and use correct structured, curvilinear, unstructured computational grids in computational problems;
ON7. To formulate the task of statistical analysis and evaluation in the chosen subject area, to select and apply statistical tools and software. To master new methods of applied and mathematical statistics for their use in analytical work:
ON8. Develop parallel computing algorithms for engineering problems and implement them in high-performance systems, develop quantum computing algorithms.
ON9. Use the methods of mathematical statistics on real data for the selection of parameters, adaptation and testing of computing systems based on real experiments
ON10.Use data mining methods based on deep learning, reinforcement learning to adapt the computational algorithm to effectively predict results

Admission Requirements

6+
87+

3 Years
Sep

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