PhD Courses in Denmark

Enrolment guidelines ”Special rules apply for this course” 1. The course is mandatory for all new PhD students at SUND from 2025. 2. This course is only for PhD students enrolled at SUND in the first six months of their enrollment. Therefore, all other ap

Enrolment guidelines ”Special rules apply for this course” 1. The course is mandatory for all new PhD students at SUND from 2025. 2. This course is only for PhD students enrolled at SUND in the first six months of their enrollment. Therefore, all other ap

Enrolment guidelines ”Special rules apply for this course” 1. The course is mandatory for all new PhD students at SUND from 2025. 2. This course is only for PhD students enrolled at SUND in the first six months of their enrollment. Therefore, all other ap

Enrolment guidelines ”Special rules apply for this course” 1. The course is mandatory for all new PhD students at SUND from 2025. 2. This course is only for PhD students enrolled at SUND in the first six months of their enrollment. Therefore, all other ap

Enrolment guidelines ”Special rules apply for this course” 1. The course is mandatory for all new PhD students at SUND from 2025. 2. This course is only for PhD students enrolled at SUND in the first six months of their enrollment. Therefore, all other ap

 To provide participants with a basic understanding of the programming environment MATLAB. Enable participants to use built-in MATLAB functions and create own scripts and functions for data evaluation and visualization.

Through this course, students obtain insights in the fundamentals of academic research practices. Particular focus is on crafting a proper academic object, formulating a good problem statement, structuring one’s data collection, and getting a first

Objectives of the Course:The course aims to provide the PhD students with foundational knowledge and practical skills in using AI and machine learning techniques for image segmentation, with a focus on applications in various fields.Learning Outcomes and

General course objectives:Make the participants able to perform a standard statistical analysis of their own data and relate the results to the practical application. The participants will be able to carry out statistical analyses using the statistical pa

General course objectives:Bayesian inversion is the technology of characterization and management of randomness in computational models of real-world applications. It blends theories and methods across stochastic analysis, statistical modeling and scienti