Do you need to turn data into a publication figure? We offer tools and confidence for the student to independently select a statistical method for research questions in their field. The course is practical and includes implementing a basic statistical analysis in R, the leading statistical programming language in bioinformatics and medical science. Furthermore, we give a brief introduction to visualization in R, with a focus on R/ggplot2. Students can bring data from their own research project, or work on data from the course.

The course content lean on Design thinking ideology and methodology that inform research as well as developmental work and form a practice-based foundation for innovation aimed to meet the needs of societal and scientific environments. As a student, you work  individually from your own research perspective, and get helpful insights for future research.  

The course apply a problem-oriented teaching and learning style,  with a pedagogy that enables students to take active responsibility for individual and also group learning in a multi-disciplinary context.

Progress in medical innovation stands as a catalyst for worldwide economic growth. Whether within pharmaceuticals, medical devices, biotechnology, information technology, or a fusion of these advancements, the potential advantages extend significantly to private businesses and societal well-being. However, due to long development times and rigorous regulations, these innovative concepts require a lot of financing to establish their presence in the market. Consequently, assessing the value of novel medical innovations remains crucial. The primary objective of this course is to empower researchers with the proficient capability to effectively assess the worth of emerging technologies or processes within the medical industry.

The course aim is that the doctoral student develops a theory of science approach by enabling the doctoral student to understand, employ, reflect upon and critically assess concepts and ideas of theories of science as well as their implications for in particular medical scientific practice. A further aim is to enable the doctoral student to understand, reflect upon and critically assess views on and implications of definitions of health and disease.

The course is designed to provide students and researchers with a solid understanding of functional Near-Infrared Spectroscopy (fNIRS) as a relatively new tool to measure brain activity and will emphasize both theoretical knowledge and practical skills of fNIRS. The students will gain expertise in the underlying principles of fNIRS, its instrumentation, and various analytical approaches. The primary goal is to empower students with the knowledge of this additional neuroimaging tool to design and execute advanced experiments, interpret fNIRS data effectively, and contribute to cutting-edge research in neuroscience and related fields.

The main purpose of the course is to provide the students with a solid understanding of the tools available to analyze brain structural data measured with structural magnetic resonance imaging (sMRI). The students will develop the ability to critically review results provided by different methods, to select the most adequate tools and experimental designs to answer different questions and to compare their relative advantages.

The course will introduce neuropsychological assessment in an aging population, focusing on age-related cognitive changes and their neural correlates. An additional purpose is to increase understanding of cognitive aging and how to differentiate between non-pathological cognitive aging and early signs of pathology. After the course, you will be able to define and describe common neuropsychological concepts and measurement techniques and demonstrate an overall understanding of neuropsychological investigation methodology and cognitive diagnostics in aging. The course will give you an increased understanding of cognitive aging and the complexity of differentiating between “normal” and early-stage pathological aging.

Participants receive basic and advanced knowledge of neurophysiology and information about relevant methods (e.g. evoked potentials, extra- / intracellular, patch clamp recordings). Properties of ion channels as well as cellular and network
properties of selected model systems (leech, goldfish, hippocampus) will be discussed.

This course is a basic course on advanced fluorescence microscopy imaging and correlation spectroscopy techniques for quantitative characterization of molecular transport and interactions in live cells. The purpose of the course is to give an introduction of the underlying physicochemical principles, hands-on training and an overview of applications of these specialized techniques in biomedical research. At the end of the course, the student will have hands-on experience with live-cell imaging and specialized fluorescence microscopy and correlation spectroscopy techniques. The course is suitable for doctoral students lacking training in mathematics, physics, or optical engineering who want to apply these techniques in their research.

The course reviews central concepts and topical research in stress, sleep and health. In particular, it is focused on how acute stress, chronic stress, diurnal rhythm and sleep problems affect and interact physiological systems such as the immune system, the endocrine system, cognitive processes and possible consequences for health. The course encompasses neuroscientific and other biological perspectives, and describes interventions to improve stress- and sleep related symptoms. Theoretical models and methods to understand and study stress- and sleep related processes will be applied. 

The course will be provided fully online, partly via Zoom but also taking advantage of recent digital tools such as Gather; and using Canvas as the learning platform in-between in-class sessions.

Our MATLAB-based comprehensive course is designed to equip you with the essential knowledge and practical skills to delve into biomedical image processing, specifically tailored for biological/medical and neuroimaging applications using MATLAB.

Selection will be based on:
1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation),
2) start date of doctoral studies (priority given to earlier start date)

The course provides a deeper understanding of neurodegenerative disorders from a basic to a clinical perspective. It consist of a combination of lectures, lab demonstrations and group dicussions led by experts in the field. It covers cellular and molecular pathophysiological mechanisms of neurodegenerative disorders and the mechanisms of current and/or possible future treatments. We will discuss similarities and differences between the different neurodegenerative diseases. The students will also be introduced to some powerful techniques that can be used for studying neurodegeneration, subcellular localization, and omics approaches. We will discuss advantages and drawbacks of important methods and models for studying mechanisms behind neurodegenerative disorders

SELECTION

Selection will be based on:  
1) the relevance of the course syllabus for the applicant’s doctoral project (according to written motivation). 
2) start date of doctoral studies (priority given to earlier start date).