GS-VMAS PhD Courses

Course code: PVG0044

Credits: 4

Course dates: Join continuously

The course has a dual format. One part is to actively participate in two workshops (4 hours per workshop) dealing with both oral and poster presentation techniques and the practical construction of a poster. Another part is to actively participate in >20 seminars given in the course seminar series. The seminar series will have weekly seminars during the spring and autumn semesters.

Course syllabus

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Course code: P000007

Credits: 3

Course dates: 23 Sept - 02 Dec 2025 (meetings approx. once a week)

The course focuses on primary production of animal source food and how the complete system up to farm-gate affects the environment. Different topics will be covered by experts in the fields in eight lectures followed by discussions. Relevant literature will be provided for the students to read before each lecture. The course meetings will be spread over one complete semester. The examination consists of a written summary submitted to the course leader team where the students relate their own research project to the different themes and an oral presentation given in a group session with other students. Other students will contribute with asking questions and give their perspectives on each presentation. Online participation will be facilitated.

Course syllabus

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Course code: P000007

Credits: 2

Course dates: 13 - 17 Oct 2025

The course is built around the feed cycle, i. e. the production of feed crops; their storage, handling and feeding; and the recirculation of animal wastes to new feed crops. The contribution from each step as well as the aggregated environmental impact for entire production systems are highlighted. Animal-specific properties of dairy and beef cattle, horses, pigs and poultry that are linked to environmental issues are covered. Greenhouse gases and losses of P and reactive N are the emphasized issues. Self-supplying systems serve as a model, but the actual situation with global trade of feeds, fertilizers and other inputs is also covered. The course time is equally divided between lectures and group work.

Course syllabus

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Course code: PVG0047

Credits: 3

Course dates: 13 - 24 October 2025

We will give a theoretical overview of what the One Health concept is, and why a one health approach is necessary to provide efficient solutions to the global challenges of our time. We will describe the benefits (and drawbacks) of transdisciplinary research and how transdisciplinarity is used in this context. Theoretical lectures will be mixed with presentations of successful one health cases. Methods commonly used within the one health concept will be presented, e.g. including epidemiology, bioinformatics, and qualitative research methods.

Participants will present their own research project to the group and after the first course week they will give a second presentation describing how the project could be developed using one health concept and methodology. The second week, students will be divided into groups and given the task to come up with a one health research project, and a skeleton for a research application.

Course syllabus

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Course code: PVS0141

Credits: 10

Course dates: 3 Nov 2025 - 19 Jan 2026

The course aims to give the student a solid foundation in the basic methods of bioinformatics. It will cover the theories, algorithms and practical applications of computer-based methods for analysis of DNA sequences and protein structures. The topics to be covered include: - biological databases - homology analysis - sequence analysis (with emphasis on the package EMBOSS and UGENE) - statistics and R introduction - web-based tools for analysis - the Unix operating system - phylogeny - comparative genomics - functional genomics - Next Generation Sequencing (NGS).

Course syllabus

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Course code: P000085

Credits: 3

Course dates: 19 - 30 Jan 2026

Through this course you will gain:

• A practical overview of handling data in R, including merging datasets directly from the original data files within R. During the course this knowledge will be used to automatically update illustrations and maps. Learning a proper Data handling strategy is important to minimize the usual multiple versions of the dataset(s) that are created by many students. At the same time, it is important to preserve the original data to prevent irreversible errors due to manual handling. This is of particular interest in many projects where data is added and updated continuously.
• A practical and theoretical background to choose suitable figures to convey graphically the nature of a specific dataset and what to avoid.
• An introduction for students to plot their data-points on maps in vector- and raster data formats using GIS software. Visualizing data on maps is an important part of many projects in the one health field.
• An introduction to open science, with an emphasis on reproducible data and scripts, and sharing these through DOIs. 

The course will use free software within the R environment, including packages such as tidyverse, dplyR, tidyR, and ggplot2. For GIS, QGIS will be used. For DOI and data sharing, GitHub will be used. The #tidytuesday project on GitHub will be the primary source of example datasets.

Theoretical lectures will be mixed with presentations and hands-on workshops. Students will work in groups to solve given problems that tie back to the lectures using #tidytuesday data.

A final individual project will be given where the students will use their own data (when available) or use the #tidytuesday datasets to implement the learning objectives and present their project.

Teaching will be conducted as a one week on-campus class followed by an independent project that will be presented via zoom.

Course syllabus

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Here is an overview of all courses arranged 2022 - 2025

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