This workshop provides a hands-on learning experience with a focus on a wider variety of AI tools, their ethical implications and their practical applications. The aim is to facilitate the responsible and efficient use of AI-based tools in research and academia.

Content:

• Understand the importance of using AI in research and academia and assess the benefits and risks involved
• Craft effective prompts for your research tasks
• Develop strategies to integrate AI tools into your research workflow
• Stay informed about and adapt to new developments in the field of AI

At the end of the workshop, you will receive a list of generative AI prompts useful in research and academia. There will be practice sessions during the workshop for which you will need access to AI tools, particularly ChatGPT/GPT-4o. If you do not have an account with ChatGPT/GPT-4o, alternatives like Microsoft Copilot, Google Bard or Claude.ai could also be used.

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 "Clinical Research in Child and Adolescent Psychiatry: Methods and Practice" course aims to cover a range of methodological factors in clinical trials on youths with psychiatric disorders, including psychiatric assessment and psychological as well as pharmacological treatment. The course will provide broad as well as in-depth knowledge about methodological and practical aspects of clinical psychiatric research focusing on children and adolescents. The course also addresses good clinical practice principles and Swedish and international rules and regulations relevant to clinical research involving young individuals.

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.

This course provides a solid ground in neuroscience, including cellular neuroscience, sensory and motor functions, and higher brain functions. It is intended for those lacking a basic neuroscience education. It runs in parallel with the Neuroscince course of the Bachelors programme in biomedicine. The course does not give regular course credits for doctoral students, but can be used to cover the demand of a grounding course in human physiology/pathology.

This course takes you on a journey into the exploration of how the brain shapes and enables our social and affective behaviors. We will examine key questions, such as how we learn from each other, when and in what ways social norms influence us, and how our communication and social decision-making unfold. 

The course covers the theoretical background to the brain imaging methods sMRI, fMRI, PET, EEG and MEG, such as what aspects of the human brain's structure and function they register, and the operation principles of the imaging instruments. The coursed gives the student a good understanding in how the different methods are used within in academic research as well as within health care. The course also addresses how the imaging methods can be combined in multimodal analyses, and discusses the interplay between development of theory, instrumentation, method, and applications.
The course begins with an introduction to brain imaging methods within neuroscience. In separate course modules, the course then offers the student a deeper understanding of the different methods sMRI, fMRI, PET, EEG and MEG, as well as combining them in multimodal brain imaging. Finally, the students will deepen their knowledge on a topic of their choice in an individual study project.

This course aims to introduce students to health care organization and management, and how this affects public health. There is a special focus on the opportunities offered by digitization and how these can be utilized in quality and improvement work.

The purpose of the course is to introduce the topic of artificial intelligence (AI) in mental healthcare focused on theoretical development, ethics and practical application informed by a scientific approach.

This course will elevate your AI proficiency, preparing you to actively engage in the digital evolution of healthcare. It offers a comprehensive perspective on the healthcare shift, steered by medical necessities, and bolstered by innovative artificial intelligence solutions.

This course provides students with in-depth knowledge in the field of digital health from an entrepreneurship perspective. Domains of digital health, needs-based innovation including prototyping, usability and testing as well as data management, intellectual property, reimbursement, business models, ethics and future trends will be discussed and analyzed.

Topics covered include:

• Hearing and speech perception and associated disorders (e.g., hearing loss, deafness, tinnitus)
• Vestibular function and associated disorders
• Objective electrophysiological measures: auditory and/or vestibular evoked responses (ECochG, BERA, ASSR, CERA, VEMP)
• Behavioural experiments (psychoacoustics)
• Principles of hearing rehabilitation with neural prostheses, i.e., cochlear implants
• Research methods in audiology/auditory neuroscience
• Application of methodology (in patients, if possible)
• How to design and conduct research projects

Topics covered include:

• Computational design strategies
• Differential equations
• Programming in Python
• Data analysis

Topics covered include:

• Experimental design strategies
• Fluorescent immuno-histochemistry
• Confocal Microscopy
• Intra-vital Microscopy (e.g. two-photon, three-photon, 2P-STED, ...)
• Data analysis
• Behaviour

Topics covered include:

• Tissue isolation and cryosectioning
• Immunofluorescent staining/Western blots
• Tissue isolation and cryosectioning
• Imaging (e.g. Confocal microscopy, Slide scanner etc.)
• (Semi-) automated image anaylsis (e.g. Fiji, machine learning based analysis)

Topics covered include:

• Coding: basic concepts, practical training, testing
• Foundations of sensor technologies
• Foundations of Bluetooth communication
• Usage of advanced programming interfaces (APIs)
• Analysis of time series data
• Introduction to machine learning techniques

Topics covered include:

• CRISPR/Cas9 mediated genome editing in mammalian cell lines
• CRISPRoff genome editing tools to modify activity of gene promoters
• Cloning of promoter regions and relevant proteins into reporter gene and mammalian expression vectors
• Reporter gene assays to measure activity of gene promoters or unknown DNA sequences using plate luminometer
• Chemical modification of genomic DNA for DNA methylation analysis
• Pyrosequencing for detection and quantification of DNA methylation
• Chromatin preparation and chromatin immunoprecipitation analysis
• Standard PCR and quantitative reverse transcription PCR analysis
• Transfection and expression of relevant proteins in mammalian cells
• Western blotting for protein analysis

Topics covered include:

• rAAV-guided engram labeling techniques (Cal-Light, SomCal-Light, FLARE)
• Tissue engineering (FluoClearBABB, ExM)
• Large-field superresolution microscopy
• AI-guided behavioral classification
• Multifactorial behavioral classification

Topics covered include:

• Histological preparation of rodent sensory organs
• Immunohistochemistry on mole-rat and mouse neuronal tissues
• 3D histology using tissue clearing
• Fluorescence microscopy, Light sheet microscopy
• Behavioural assessment of magnetic orientation under controlled conditions

Topics covered include:

• Assessment of memory and imagination in patients with neurodegenerative dementias and related to aphantasia
• Rating of patients’ memory reports
• Analysis of patient data
• Writing summary reports

Topics covered include:

• animal models to study epileptogenesis
• *omics analyses of human epileptic specimen
• Screening analyses for classical auto-antibodies and new candidates inpatients suspicious for limbic encephalitis
• Analyzing the functional role of patient-derived auto-antibodies in epilepsy in vitro und in vivo
• Analyzing synchronous network activity in vitro (multi electrode array; MEA)
• CrispR-Cas systems to interfere with epileptogenesis
• Generation of animal models to study limbic encephalitis
• Neuropathology in experimental LE

Topics covered include:

• Hypothesis driven planning and design of experiments for research project
• Cloning, colony cracking and transfection
• Cell culture and life cell imaging
• Imaging and data analysis
• Application of techniques depend on individual working plan

Topics covered include:

• How to design, code (C#, Unity) and conduct virtual reality experiments
• How to record, time-sync and real-time access physiological data streams during virtual reality experiments (based on LabStreamingLayer)
• How to analyse psychophysiological data (e.g.: wireless EEG, EMG, EDA, HRV or Eyetracking), using common Matlab-packages such as EEGLAB or LEDALAB

Topics covered inlude:

• Cognitive neuroscience of social perception and cognition
• Dysfunctions of social perception and cognition
• Research methods in social neuroscience (signal detection theory; metacognition; experimental psychology; classification methods)
• Experimental design

Students will have the opportunity to:

• work with various model systems (e.g. different cell lines, C. elegans and tissue from transgenic mice
• perform different biochemical analysis assays (e.g. Western blot, RT-PCR) 
• immunohistechemical stainings and confocal imaging

In addition to hands-on practical methods, students will attend scientific lectures and seminars.