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| Course title | City | Start date | Credits |
|---|---|---|---|
| Introduction for new PhD students at SUND | February 2026 | 2 ECTS | |
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Graduate School of Health and Medical Sciences at University of Copenhagen
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 |
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| Introduction for new PhD students at SUND | March 2026 | 2 ECTS | |
|
Graduate School of Health and Medical Sciences at University of Copenhagen
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 |
|||
| Introduction for new PhD students at SUND | March 2026 | 2 ECTS | |
|
Graduate School of Health and Medical Sciences at University of Copenhagen
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 |
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| Introduction MATLAB with examples from Health Science | Aarhus | February 2026 | 4,2 ECTS |
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Graduate School of Health Sciences at Aarhus University
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. |
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| Introduction to Academic Practices | Copenhagen K. | January 2026 | 3 ECTS |
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The Royal Danish Academy, the PhD School
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 |
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| Introduction to AI and Machine Learning in Image Segmentatio... | Roskilde | - | 3 ECTS |
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Graduate School of Technical Sciences at Aarhus University
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 |
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| Introduction to applied statistics and R for PhD students | Kgs. Lyngby | - | 5 ECTS |
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DTU Department of Informatics and Mathematical Modeling
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 |
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| Introduction to Bayesian inverse problems | Kgs. Lyngby | - | 5 ECTS |
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DTU Department of Informatics and Mathematical Modeling
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 |
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| Introduction to Clinical Epidemiology | Aarhus | February 2026 | 3,3 ECTS |
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Graduate School of Health Sciences at Aarhus University
To introduce PhD students to the fundamentals of design and analysis of clinical epidemiology research. Each concept will be introduced in a lecture. Students will then carry out in-class exercises applying the fundamental principles introduced in the lec |
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| Introduction to Complex Systems Approaches in Public Health | April 2026 | 3,1 ECTS | |
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Graduate School of Health and Medical Sciences at University of Copenhagen
Enrolment guidelines This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member faculties. All other participants must pay the course fee.Anyone can apply for the cour |
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