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Supplementary rules for the content of the educational component of the PhD-programme at the Department of Mathematics

Together with the work on the thesis, the educational component must provide the necessary academic breadth and specialization.

Specialization in Mathematics: For the specialization in mathematics, there is a requirement for breadth in the educational training component. 20 credits of the total credits included in both Master's- and the PhD-programme’s educational training component, must be outside of the candidate's field of expertise. The requirement of having 20 credits outside the field of expertise is absolute and means that those who have no breadth from their educational component on the Master's level must take 20 credits in their educational training component on the PhD-level.

Specialization in Mechanics: There are no special requirements beyond the Department's general requirements.

Specialization in Statistics and Data Science: If the candidate does not have STK4011 – Statistical Inference Theory or STK-IN4300 – Statistical Learning Methods in Data Science (or equivalent subject) in his or hers educational training component on the Master's level, it is recommended to include either STK9011 – Statistical Inference Theory or STK-IN9300 – Statistical Learning Methods in Data Science as a part of the educational training component on the PhD-level.

Specialization in Finance, Insurance and Risk: There is a requirement of having a certain breadth in the educational training component at the PhD-level. This means that at least 20 credits have to be outside the core area of ​​the thesis. If the candidate has completed his or her Master's degree within another subject area, the breadth requirement is considered covered by this.

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Published June 21, 2019 1:15 PM - Last modified Feb. 2, 2021 10:17 AM