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Learning Opportunity: Computational Engineering, MS

Computational Engineering, MS

Course Information

A two-year graduate study programme in computational engineering at the Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, School of Engineering and Natural Sciences of the University of Iceland. The study programme is 120 ECTS and is a fully accredited MS degree. The study programme is composed of 60 ECTS in a research project and 60ECTS in courses. The standard requirement is that students have completed a BS in computer science, engineering, mathematics or physics, but they must also have fullfilled specific requirements in mathematics and computer science

Knowledge, competence and skills
On completion of the study programme the student can demonstrate knowledge, skills and competence as detailed below:

1. Knowledge and understanding
1.1. The knowledge of the student covers those diciplines that are required to carry the professional title of an engineer in Iceland.
1.2. The student has understanding of recent knowledge within the fields of mathematics and computer science that is most applicable to the task of constructing computational models within some specific dicipline, e.g. physics, economics or biology.
1.3. The student has mastered concepts and tasks within some specific dicipline, and has experience of cooperating with experts within such a field on the construction of computational models.
1.4. The student has deeper understanding of the limitations of compuational models and possible consequences of these limitations.

2. Type of knowledge
2.1 The student has important evidence of problems and issues within a specific field of knowledge within computational engineering and on its application to another dicipline, derived from the newest information and research in that field.
2.2 The student has deepened and broadened his knowledge base in numerical analysis, statistics, operation research and computational intelligence.

3. Practical competence
3.1. The student has developed the ability to work independently, can make autonomous professional decisions and is capable of targeted presentation, both orally and in writing.
3.2. The student can define complex subjects, define goals, make a work plan and follow it.
3.3. The student is trained to analyse large computational modeling projects and to propose independent reasoned solutions for such projects.
3.4. The student has received further training in adopting new software technology.

4. Theoretical skills
4.1. The student can organise his own study of specified subjects of interest and successfully apply the appropriate research processes.
4.2. The student is familiar with research methods in his academic field and is trained in reading research papers and their conclusions.
4.3. The student is competent to integrate diverse knowledge, can use diverse sources and can apply them in his own study.
4.4. The student has a clear understanding of what are thorough and recognised academic practices and can argue in favour of his view.
4.5 The student has an augmented ability to apply abstract notation and methods in analysing a problem.

5. Communication competence
5.1. The student is independent and shows initiative in his work.
5.2. The student can work in groups, manage other people's work and shoulder responsibility for that work.
5.3. The student can clearly present complex academic matters in the field of computational engineering, both orally and in writing.
5.4. The student understands debatable issues that may arise in the context of computational models, technical, societal annd ethical and can clarify these for different types of co-workers.

6. General academic competence
6.1. The student has the necessary competence and training to take on autonomous research in this field.
6.2. The student has gained self-confidence, broad-mindedness and critical thinking that helps him maintain his knowledge in study and in work.

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