Examination arrangement

Course content

The course is suitable for PhD graduates, who will do research within advanced maritime operations focusing on system analysis, modeling, simulation and visualization, aimed at design, virtual prototyping, operational training and life cycle maintenance and service. The teaching is mainly conducted as a self-study with joint colloquia/seminars to discuss relevant methods and topics, and with invited guest lectures by national or international researchers in the field. The purpose is that PhD candidates should be able to specify and learn advanced methods and theory within which are not covered in the MSc. programs or in other PhD subjects at the university. Normally, students will define an individual specific study topic, agreed with the course responsible/supervisors at the start of the course. Key topics will be in the application of digital technology, data collection, data transfer and data analysis.

Learning outcome

Knowledge: After completing the course, the students will be able to demonstrate detailed knowledge of the studied subject at an advanced level within demanding maritime operations focusing on analysis, modeling, simulation and visualization, aimed at design, virtual prototyping, operational training and / or condition monitoring.
Skills: After completing the course, the students should be able to:
-explain the theoretical background in the selected subject and relate this logically and systematically to the dissemination of theoretical models for analyzes of the given problem.
-argue for choice of methods and display skills using selected methods
-show through an applied case example and some results applying the selected methods
General competence: Through participation and completion of the course the students shall:
-write a journal article with clear and concise presentation of theory, application, results, discussion and conclusions, and verbally present the results of a specific case study
-conduct academic studies and publish research results in a good research ethical way.

Learning methods and activities

The teaching is generally conducted as a self-study with joint colloquiums and seminars where relevant topics are discussed between the students and scientific resources, including invited guest researchers. The course will be offered every semester when enough students have signed up. To pass the course, a minimum score of 70 percent is required (70 out of 100 points).
For special case, the learning activity could be organized individually based on the discussion between Ph.D candidate and course responsible.

Recommended previous knowledge

Ph.D candidates on Engineering with basic knowledge in programming and data analysis, modeling of dynamic systems, basic domain knowledge within the chosen specialization topic.

Course materials

Agreed at the start of the course based on defined topics and/or by the organized guest lectures. The self-study will be based on a reading list containing general material on the core topics, and some individual defined reading specified by the individual selected topic, and all defined at the beginning of the course.