Data and Physics Driven Modelling (MOD900)
Background formation PhD course. The course is intended to enhance the background level of the student to a suitable level to conduct Research on the candidate's topic.
Course description for study year 2025-2026. Please note that changes may occur.
Facts
Course code
MOD900
Version
1
Credits (ECTS)
10
Semester tution start
Spring, Autumn
Number of semesters
1
Exam semester
Spring, Autumn
Language of instruction
English
Content
The purpose of this course is to broaden the PhD Fellow's knowledge beyond the main PhD dissertation topic. The PhD Fellow will, on his/her own accord, work through the curriculum with the intent of developing a broad and solid understanding of modeling as it applies to computational engineering approaches. The candidate will also do independent research in the topic area.
Learning outcome
Knowledge:
- Upon completion of the course the PhD candidate should understand the fundamental principles of data science and modeling as applied to computational engineering as well as understand how principles applies within research.
Skills:
- Skills needed to build a good basic model and to use it in generating new informed insights
- Be able to apply and construct models and to use the most important elements at different level of scale in the face of uncertainty.
General competence:
- The PhD candidate should understand fundamental logical principles and analyses and be able to communicate their choices and recommendations clearly.
Required prerequisite knowledge
None
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Oral exam | 1/1 | Passed / Not Passed | All |
Individual oral exam
Coursework requirements
Achieve a grade B or better in MOD500, MOD550 or PET685
Course teacher(s)
Course coordinator:
Enrico RiccardiCourse coordinator:
Reidar Brumer BratvoldHead of Department:
Alejandro Escalona VarelaMethod of work
Lectures and independent work
Open for
PhD Students
Course assessment
The faculty decides whether early dialogue should be conducted in all or selected groups of courses offered by the faculty. The purpose is to gather feedback from students for making changes and adjustments to the course during the current semester. In addition, a digital evaluation, students’ course evaluation, must be conducted at least once every three years. Its purpose is to collect students` experiences with the course.