DTE-3900 Master Thesis – M-IT - 30 stp

The master thesis project represents the conclusion of the master study, where the students get an opportunity to apply the knowledge acquired in preceding courses.

The thesis assignment is formulated by the supervisor, individually or after discussion with the student and/or external participants. The institute offers a wide range of project assignments within relevant and pertinent topics, based on internal or external research activities, but the student may also suggest assignments based on their own interests or according to requests from the industry. The assignments may also be extensions of project works completed previously in the study, however, with broadened problem definitions.

The project assignment may in general contain both theoretical and practical elements, such as mathematical modelling, system analysis, theoretical derivations, programming, and practical development. The project is individual, and the work should be performed at UiT - Campus Narvik. If the project assignment is formulated in collaboration with a specified external partner, it is possible to arrange for the student to work at the partner’s location for parts of the project period.

Guidelines for the master thesis project work are formulated by the master's degree programme Applied Computer Science at UiT Narvik.

Prerequisites: Completed a satisfactory number of courses (corresponding to at least 80 ECTS) in the pertaining program or equivalent. Each candidate must be approved by the programme.

Recommended prerequisites: An undergraduate bachelor engineering degree in computer science or equivalent.

The goal of the master thesis project gives the student competence to carry out an individual project within a selected topic, relevant and pertinent to the master programme. The student will also acquire a broad knowledge of the topic through literature surveys of previous work within the field and related fields, and a profound knowledge through solving a specified problem. The final result of the project is a scientific report (thesis) with a presentation of the problem itself, the suggested solution and a discussion of employed techniques and the results.  

After passing the course, students will have the following learning outcomes:

Knowledge and understanding:

After completing the course, the student:

• has advanced knowledge within the academic field of some applied mathematics, physics and engineering and specialized insight in a limited area within the of computer science (K1)
• has some knowledge of different theories and methods in the field of computer science (K2)
• can apply some knowledge to new areas within the academic field of numerical and analytical calculations, computations, simulations, systematic design process, computational methods, artificial intelligence, geometric modeling, computational geometry, computer science (K3)
• can analyze academically some problems on the basis of the history, traditions, distinctive character and place in society of the academic field in computer science (K4)

Skills:

After completing the course, the candidate:

• can analyze and deal critically with information and use them to structure and formulate scholarly arguments (S1)
• can analyze existing theories, and interpretations in the field of computer science and work independently on practical and theoretical problems (S2)
• can use relevant methods in computer science for research and scholarly in an independent manner (S3)
• can carry out an independent, limited research or development project under supervision and in accordance with applicable norms for research ethics (S4)

Competence:

After completing the course, the candidate:

• can analyze relevant academic, professional and research ethical problems (GC1)
• can apply the knowledge and skills within computer science in new areas in order to carry out advanced assignments and projects (GC2)
• can communicate extensive independent work and master the domain language and some terminology of the academic field of computer science (GC3)
• can communicate about academic issues, analyses and conclusions in the field of computer science, both with specialists and the general public (GC4)
• can contribute to new thinking and innovation processes (GC5)

As the topic of the master thesis is not the same for each task, some of "Learning outcomes, skills and attitudes" points mentioned above will not necessarily be fulfilled. Thus, the learning outcome is somewhat dependent on the topic of the master thesis.  

Project run by the students under guidance by one or more supervisors.

Teaching and Examination Language: The master thesis can be written in Norwegian or English. This point must be clarified when the project begins.

Eksamen og vurdering

Individual work. Participation in group project work can be granted depending on the scope and definition of the task.

The work is initiated through suggestions of possible topics given by the scientific staff. The students are also strongly encouraged to discuss possible alternatives within these suggestions with the relevant professors. It is normally required that actual topics are related to one or more of the subjects included in the study program or the staff’s on-going research work.

Each student (or student group) will have one or more supervisors through the entire working period, but once the project assignment is given, the students are responsible for management of the project themselves.

During the first three weeks it is normally required that the students prepare a pre-study report including an analysis of the assignment, definitions of activities and work packages and a time schedule. The plan should also include milestones and agreed progress meetings with the supervisor(s) and, when relevant, the contact person from the external partner.

The final report with enclosures will be assessed as a whole based on its scientific contribution. The assessment will usually focus on the following criteria:

Accomplishment in accordance with the pre-defined assignment, academic with regard to data collection, methodology, data processing, data utilization, comments, conclusions, independency, originality; structure, outline, editing, context; style of writing, orthography; illustrations; documentation (sources, citations, references); complexity.

The grades are based on the ECTS-system: A (excellent), B (very good), C (good), D (satisfactory), E (sufficient) and F (fail).

There will not be arranged a re-sit exam for this course.

The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.