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# Mathematical Sciences - master

## Facts

Duration: | 2 År |

Credits (ECTS): | 120 |

Qualification: | Master of Science in Mathematical Sciences. |

Admission requirements: | Bachelor´s degree (180 ECTS) in Mathematics, Statistics, Physics or other relevant degree, with a minimum of 80 ECTS in mathematics and/or statistics. A minimum grade average comparable to a Norwegian C (3.0) in the ECTS scale |

Application deadline: | Nordic applicants: 15th of April/1st of November International applicants: 15th of November |

Application code: | 4010 |

## Programme description

The academic contents of the program are geared towards modern issues in mathematics and statistics, and towards the appliance of mathematics and statistics in technology and other natural sciences. The candidates will gain relevant skills within programming, data processing, analytical problem solving and quantitative analysis.

The master´s program consists of 20-40 ECTS in specialization courses and up to 20 ECTS in elective courses. The mandatory courses are 20 ECTS in Introduction to mathematical research. The master program concludes with a master’s thesis of 60 ECTS.

Examples of course combinations for students with interests in applied mathematics, differential geometry, algebra and statistics are found in the Study plan below.

Courses from other Universities, both national and international can be included in the study program.

## Programme structure

10 ects | 10 ects | 10 ects | ||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

1. sem. (autumn) | MAT-3001 Introduction to Mathematical Research 1 - 10 stp. | |||||||||||||||||||||||||||||

2. sem. (spring) |

## Learning outcomes

**After completing the study programme, the candidate will have achieved the following learning outcomes:**

**Knowledge**

The candidate:

• has advanced knowledge within mathematical areas such as statistics, algebra, geometry or applied mathematics

• has solid knowledge about fields close to the chosen main area

• has sufficient knowledge of mathematics to teach in senior high school

• has solid knowledge about fields close to mathematics and statistics, such as physics or computer science

• has thorough knowledge of mathematical or statistical methods in theory and practice and can analyze academic problems on the basis of traditions in the academic field

• can apply mathematical or statistical methods in new areas of natural and social science

**Skills**

The candidate:

• can enter complicated problem issues, uncover structures and formulate precise problems, find suitable analytical and/or numerical solution methods, and interpret the solutions

• has good practical skills in using relevant programming tools

• can use existing literature in an active way to understand the work of other scientists, and as support to solve own mathematical problems

• can use mathematical or statistical methods in theory and practice, and make an independent judgment of the applicability of theory and models for a given problem

• can carry out an independent, limited research project under supervision and in accordance with applicable norms for research ethics in the mathematical sciences

**General Competence**

The candidate:

• has solid knowledge of a broad variety of mathematical and statistical methods and techniques for analysis and problem solving

• has acquired good theoretical insight and the ability to apply mathematical theory, methods and techniques to solve problems

• possesses necessary qualifications for work within industry, technology, science, information technology, and schools.

• can apply knowledge within mathematics and statistics on problems and questions arising within social and natural sciences

• can cooperate in an interdisciplinary way with other specialists

• can find precise and scientific formulations, in oral and written language

• can do independent scientific work and formulate the contents of the work within the framework of the terminology of mathematics and statistics

• can make knowledge-based judgments on general scientific issues and communicate these in public.

• can contribute to new thinking and innovation processes in the field of mathematics and statistics

## Teaching and assessment

The courses in the study program mostly consists of lectures, seminars and exercises.

All academic staff who teach the study program are active researchers in various research projects. The courses are based on relevant research and are related to the department’s research activity. Special curriculums and the master's thesis are supervised on an individual basis by the department's academic staff.

Form of assessment varies between portfolio assessments, home exams, reports, oral and written exam. In some courses, mandatory assignments must be approved for exam access.

After submitting the master's thesis, it is assessed, and normally within 6 weeks an oral presentation and examination is held. This may influence the final mark.

## Language of instruction

## Exchange possibilities

Exchange with other Norwegian or foreign institutions is encouraged in the two first semester. Several exchange agreements and stipend arrangements are available at UiT. The department has several exchange agreements that are suitable for master's students.

The program board must preapprove the planned courses at external institutions.

We recommend exchange in the second semester. The mandatory course MAT-3002 can be exchanged with another relevant course at the exchange University, or the students can follow this course digitally and take 20 credits at the exchange University.

## Job prospectives

Through the program, the students will acquire broad competence that qualifies them for work in different areas and sectors. They train in problem-solving using systematic and analytical methods, which will make them attractive candidates for research, development and management. There are development and innovation projects that require competence in the mathematical sciences in renewable energy, climate adaptation, information technology, economics, insurance, finance and banking, biotechnology and medical technology.

There is an increasing need for personnel who can process and analyze data, and our society sees a growing demand for competence in modeling and analyzing complex problems within different sectors and fields.