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BEGIN:VEVENT
DTSTART;VALUE=DATE:20261005
DTEND;VALUE=DATE:20261007
DTSTAMP:20260915T101811Z
CREATED:20260915T101811Z
LAST-MODIFIED:20260915T101811Z
UID:10001847-1791158400-1791331199@ddsa.dk
SUMMARY:Method comparison\, reliability and agreement
DESCRIPTION:Welcome to Method comparison\, reliability and agreement \nProgram: BEN (also relevant for B\, CPM\, CSLTM\, and HES)  \nDescription: \nThe course will focus on the importance of method comparison studies when evaluating new clinical and experimental methods. The course will describe how method comparison studies are designed and how obtained results are analysed and described. Application of analytical measures such as Coefficient of Variance\, Intra-Class Correlation\, differences in means\, and Bland-Altman’s limits of agreement\, inter-rater reliability\, observer agreement\, test accuracy and sample size estimation will be discussed. The aim of the course is to provide the participants with a toolbox that enables them to perform and analyse method comparison studies. This advanced course in biostatistics assumes knowledge of basic methods in biostatistics\, including the concepts of hypothesis testing\, and basic study designs. The course is designed for researchers working in both clinical and experimental settings. \nFor additional information\, updates\, and registration\, please refer to AAU PhD Moodle via the link provided on the right side of this page. \nDisclaimer:\nDDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/method-comparison-reliability-and-agreement/
CATEGORIES:PhD Course
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20261006
DTEND;VALUE=DATE:20261009
DTSTAMP:20260728T114700Z
CREATED:20260728T114700Z
LAST-MODIFIED:20260728T114700Z
UID:10001892-1791244800-1791503999@ddsa.dk
SUMMARY:R-kursus for begyndere
DESCRIPTION:This course provides students\, researchers\, and PhD candidates with a foundational introduction to coding in R. Over three days\, participants will be guided through six modules of 3–4 hours each\, combining short lectures with hands-on exercises and instructor support. The first two days consist of in-class lectures and exercises\, where the last day is a full day of coding using everything learned during the course.  \nThe course covers essential topics\, including: \n\nR syntax and fundamental functions\nNavigating RStudio\nData handling and aggregation\nCreating plots and tables\nWriting functions and simple algorithms\nUsing R’s help features and effective Google search strategies\nBasics of survival analysis\nStructuring a project in R\nAnd more\n\nThe course is designed for participants with no prior programming experience who wish to gain practical coding skills and apply R to their own projects or research. \n Disclaimer:DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/r-kursus-for-begyndere/
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261021
DTEND;VALUE=DATE:20261024
DTSTAMP:20260728T114700Z
CREATED:20260728T114700Z
LAST-MODIFIED:20260728T114700Z
UID:10001893-1792540800-1792799999@ddsa.dk
SUMMARY:Translational clinical precision medicine – a focus on translational biomarkers & digital health
DESCRIPTION:Omics technologies—genomics\, transcriptomics\, epigenetics\, proteomics\, and metabolomics — are crucial for bridging basic research with clinical application.  \nThis PhD course emphasizes translational clinical science and big data analysis\, combining theoretical insights with practical training. Students will learn to design ethical approved clinical studies and apply advanced bioinformatics to analyze complex omics data with clinical data. Real-life examples from autoimmune disorders\, neurodegeneration\, and chronic pain will illustrate how omics can identify biomarkers\, stratify patients\, and guide targeted therapies for improved patient outcomes. \n Learning objectives:  \n\nApplication of multiOMICs in translational health and medical science. \nStatistical evaluation and presentations of Omics data in scientific publications\nBioinformatice processing and data integration of Omics data\n\n Disclaimer:DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/translational-clinical-precision-medicine-a-focus-on-translational-biomarkers-digital-health/
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261022
DTEND;VALUE=DATE:20261023
DTSTAMP:20260909T080056Z
CREATED:20260909T080056Z
LAST-MODIFIED:20260909T080056Z
UID:10001941-1792627200-1792713599@ddsa.dk
SUMMARY:Population Health Science: Principles for Research and Action
DESCRIPTION:Welcome to Population Health Science: Principles for Research and Action \nProgram: Epidemiology & Biostatistics \nDescription: \nProfound inequities in health persist globally\, shaped by social\, economic\, and environmental conditions that extend far beyond individual behaviors or biology. Addressing these challenges requires a shift in perspective – one that considerers the broader forces influencing health across populations. \nPopulation health science offers such a perspective. As an interdisciplinary field\, it examines how health is distributed within and across groups\, and what drives these patterns. By moving beyond individual-level risk factors\, it provides a framework for understanding the societal conditions that produce health and disease. \nPurpose and scope: \nThis course introduces population health science as a conceptual and methodological foundation for understanding how health is produced and distributed across populations. The course encourages students to critically examine how research questions are framed\, how evidence is generated\, and how findings can inform action. Emphasis is placed on designing research that is not only scientifically rigorous but also capable of informing policy\, guiding programs\, and shaping public health practice. \nLearning objectives \nBy the end of the course\, PhD students will be able to: \n\nApply the nine foundational principles by Galea and Keyes to the design and interpretation of population health research\nFormulate and identify relevant research questions with potential for improving population health\nCritically assess how health and disease are distributed across populations and the factors that shape these patterns\nUnderstand key conceptual models in population health\, including multilevel frameworks\, life course perspectives\, and dynamic systems approaches\nEvaluate the social determinants of health\, including social\, economic\, environmental\, and structural influences\, and health inequity\nApply a causal architecture approach to identify and prioritize the most impactful causes for population health\nUnderstand the principles of prevention and assess their relevance to population-level health improvement.\n\nFor additional information\, updates\, and registration\, please refer to AAU PhD Moodle via the link provided on the right side of this page. \nDisclaimer:\nDDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/population-health-science-principles-for-research-and-action/
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261123
DTEND;VALUE=DATE:20261128
DTSTAMP:20260909T074836Z
CREATED:20260909T074836Z
LAST-MODIFIED:20260909T074836Z
UID:10001902-1795392000-1795823999@ddsa.dk
SUMMARY:Smart Battery: Hardware design\, modeling\, intelligent estimation and control
DESCRIPTION:Welcome to Smart Battery: Hardware design\, modeling\, intelligent estimation and control \nDescription:  \nLithium-ion batteries have revolutionized energy storage across various applications\, particularly in the rapidly growing field of e-mobility. As the demand for safer\, more reliable\, and intelligent energy storage systems increases\, the concept of “Smart Battery (SB)” has emerged as a promising solution. This comprehensive five-day course delves into the cutting-edge world of smart battery technology\, combining hardware design with battery modeling and artificial intelligence (AI)-based state estimation and control. \nThe course begins by exploring the integration of power electronics and intelligent control into the cells. This is done by using a half-bridge circuit connected across the cell terminals. The course introduces the operation of the SB with the integrated half bridge circuit while also giving a detailed overview of the state-of-the-art battery management systems\, chargers/ charging methods. This discussion evolves into the advantages of the SB in making smart BMS and energy efficient charging methods and lifetime improvement. The design of the SB\, optimal device selection\, PCB design for different geometries of the cells (prismatic\, pouch and cylindrical ) will be discussed. The SB also has intelligent control and the course introduces the communication architecture and controller selection for the SB management systems. Simulation exercises in Simulink/Plecs/LTSpice will be used as tools to understand and appreciate the SB concept and hardware architecture. \nBuilding on this hardware knowledge\, the course then transitions into the realm of modeling for Lithium-ion batteries\, and artificial intelligence applications in their state estimation. Due to the complex electrochemical reaction of the battery\, the battery performance parameters show strong nonlinearity with aging. Therefore\, as the main technologies in BMS\, accurate modeling\, battery state estimation\, lifetime prediction and balancing remain challenges. AI technologies possess immense potential in inferring battery state\, and can extract aging information (i.e.\, health indicators) from measurements and relate them to battery performance parameters\, avoiding a complex battery modeling process. Therefore\, this course aims to introduce the application of AI in Smart Battery modeling and state estimation. Especially\, students will explore battery modeling methods including equivalent circuit model and electrochemical model\, and various AI algorithms in estimating and predicting crucial battery parameters such as state of charge\, state of health\, state of temperature\, and remaining useful life. Data preparation\, preprocessing\, and AI model training and selection\, multidimensional balancing and state control will be covered. \nThis course will combine both theoretical lecturers\, exemplary introduction\, and hands-on exercises. Multiple tools like MATLAB/Simulink\, Plecs\, LTSpice\, and Python will be used. The students are expected to gain knowledge of establishing smart battery systems as well as the trend in next-generation BMS design. By the end of the course\, students will have a comprehensive understanding of both the hardware and software aspects of smart batteries\, enabling them to contribute to the development of more reliable and intelligent energy storage solutions for the future of e-mobility and beyond. \nPrerequisites: Fundamental understanding of characteristics of Li-ion batteries\, and familiar with programming using MATLAB\, Python and any circuit simulator such as Plecs or Spice. Note: the course language is English. \nFor additional information\, updates\, and registration\, please refer to AAU PhD Moodle via the link provided on the right side of this page. \n \nDisclaimer:\nDDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/smart-battery-hardware-design-modeling-intelligent-estimation-and-control/
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20261203
DTEND;VALUE=DATE:20261205
DTSTAMP:20260909T074715Z
CREATED:20260909T074715Z
LAST-MODIFIED:20260909T074715Z
UID:10001825-1796256000-1796428799@ddsa.dk
SUMMARY:Fifth symposium on the advances in biomedical engineering and neuroscience
DESCRIPTION:Welcome to Fifth symposium on the advances in biomedical engineering and neuroscience \nProgram: BEN ***mandatory course **** \nDescription: \nThe course has a focus on disseminating the most relevant and recent achievements within biomedical and engineering science to address relevant health care problems. This course will be organized annually and will include a series of lectures from internationally recognized speakers and from speakers from Aalborg University that are experts within the field. The invited experts will be researchers at a level higher than PhD candidates\, such as postdoctoral fellows\, senior researchers\, or professors. During the symposium\, some time will be dedicated to the facilitation of interaction between the speakers and participants. The detailed agenda of the course will be provided on the course web site. Main topics can include electrophysiology\, psychophysics\, bio-signal processing\, biostatistics\, rehabilitation technology\, machine learning\, physiological modeling\, decision support\, big data\, image analysis and computational neuroscience but also topics relevant for the life as a PhD student such as management of a research project\, risk analysis and mitigation etc. \nFor additional information\, updates\, and registration\, please refer to AAU PhD Moodle via the link provided on the right side of this page. \nDisclaimer:\nDDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.
URL:https://ddsa.dk/event/fifth-symposium-on-the-advances-in-biomedical-engineering-and-neuroscience/
CATEGORIES:PhD Course
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