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X-WR-CALDESC:Events for DDSA
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TZID:Europe/Copenhagen
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20241112
DTEND;VALUE=DATE:20241120
DTSTAMP:20260415T011505
CREATED:20240424T084107Z
LAST-MODIFIED:20240424T084107Z
UID:10001166-1731369600-1732060799@ddsa.dk
SUMMARY:REDCap databases for clinical research (12/11 + 19/11 2024)
DESCRIPTION:REDCap is an increasingly popular browser-based database platform for data collection in clinical research. It offers an intuitive user interface for building custom data collection instruments for clinical research projects. Instruments can be filled by the researchers themselves\, or can be enabled as surveys that can be filled by project participants themselves. With complete audit trail on all data transactions and detailed user rights and access control management\, REDCap lives up to Danish legislation concerning the handling of personal and sensitive data.\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/redcap-databases-for-clinical-research-12-11-19-11-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20241023
DTEND;VALUE=DATE:20241025
DTSTAMP:20260415T011505
CREATED:20240424T084102Z
LAST-MODIFIED:20240424T084102Z
UID:10001164-1729641600-1729814399@ddsa.dk
SUMMARY:Basic methodological concepts in clinical observational and interventional research (23-24/10 2024)
DESCRIPTION:The following elements will be dealt with: -Aspects that are common for most research designs (e.g. research questions\, study material\, data retrieval\, and approach to statistical analysis)   -Specific ‘needs’ for various research designs (e.g.  the differences between observational and association studies\, cross-sectional and prospective studies\, cohort studies and comparative studies) – Important issues to ensure external and internal validity of data (e.g. representativeness\, random allocation\, types of bias\, validity of data\, confounding/modifying factors\, and transparent data reporting)\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/basic-methodological-concepts-in-clinical-observational-and-interventional-research-23-24-10-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240921
DTEND;VALUE=DATE:20240925
DTSTAMP:20260415T011505
CREATED:20240424T083842Z
LAST-MODIFIED:20240424T083842Z
UID:10001162-1726876800-1727222399@ddsa.dk
SUMMARY:Design and analysis of epigenome-wide association studies (EWAS) ( 21-24/9 2024)
DESCRIPTION:The etiology of complex diseases concerns not only the DNA sequence variation of a gene\, but most importantly also the functional regulation of the gene triggered by specific environmental stimuli. Epigenetics is a newly emerging field of genetic study that focuses on the dynamic aspects of gene activity regulation under given environmental conditions\, a very hot topic in many areas of medical research. This course focuses on the design and analysis of epigenomic studies using high-throughput microarray technology with issues concerning study design\, biosample collection\, data preprocessing\, normalization\, quality control\, statistical and bioinformatic analyses\, biological pathway-based analysis and functional interpretation. Students are introduced to the cutting-edge development in epigenetic analysis of human diseases and learn about epigenomic data structure\, state-of-the-art data analysis with multiple free software packages.\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/design-and-analysis-of-epigenome-wide-association-studies-ewas-21-24-9-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240918
DTEND;VALUE=DATE:20241011
DTSTAMP:20260415T011505
CREATED:20240424T084026Z
LAST-MODIFIED:20240424T084026Z
UID:10001165-1726617600-1728604799@ddsa.dk
SUMMARY:Data management plan and responsible handling of research data (18/9-20/9 + 10/10 2024)
DESCRIPTION:The participants will through creating a data management plan be introduced to central elements of data management in research projects\, workflows\, relevant legislation\, principles and standards for data documentation and data control\, preparing quantitative data for analysis and relevant legislation in relation to management and safekeeping of research data.\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/data-management-plan-and-responsible-handling-of-research-data-18-9-20-9-10-10-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240909
DTEND;VALUE=DATE:20240920
DTSTAMP:20260415T011505
CREATED:20240424T084112Z
LAST-MODIFIED:20240424T084112Z
UID:10001167-1725840000-1726790399@ddsa.dk
SUMMARY:Machine learning with sports and health data - Introduction and practical implementation in R (9/9 + 12/9 and 16/9 2024)
DESCRIPTION:Over the last five to ten years machine learning (ML) methods has gained widespread use with both sports and health data. ML methods can be used with both accelerometry or heart rate data for health or sports purposes or for simple clinical studies to find important patterns in the data. The possibilities seem almost endless. An important strength of the ML methods is that it can model highly complex data\, which is common attribute of most sports and health data. However\, the introduction of engines like the ChatGPT or Bard also suggests that understanding the strengths and weaknesses of this branch of statistical methods is important to disseminate quality health and physiological information from the sports and health data.\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/machine-learning-with-sports-and-health-data-introduction-and-practical-implementation-in-r-9-9-12-9-and-16-9-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240522
DTEND;VALUE=DATE:20240525
DTSTAMP:20260415T011505
CREATED:20240424T082755Z
LAST-MODIFIED:20240424T082755Z
UID:10001159-1716336000-1716595199@ddsa.dk
SUMMARY:An Introduction to Genomics in Health Science (22-24/5 2024)
DESCRIPTION:This 3-day course aims at introducing to biomedical researchers a foundational understanding of genomics\, epigenomics and transcriptomics\, laboratory techniques\, and motivating practical applications in disease and health researches. \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/an-introduction-to-genomics-in-health-science-22-24-5-2024/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240501
DTEND;VALUE=DATE:20240601
DTSTAMP:20260415T011505
CREATED:20240424T081035Z
LAST-MODIFIED:20240424T104758Z
UID:10001184-1714521600-1717199999@ddsa.dk
SUMMARY:Data-Driven Robot Control
DESCRIPTION:Title: Data-Driven Robot Control\n The Maersk Mc Kinney Moller Institute\, SDU Robotics\n Teaching language: English\n Teachers: Christoffer Sloth chsl@mmmi.sdu.dk / Inigo Iturrate inju@mmmi.sdu.dk\n ECTS: 2.5 ECTS\n Period: May 2024\n Offered in: Odense \n Prerequisites\n It is recommended that students participating in the course have: \na.                         basic knowledge in control of robots \nb.                         basic knowledge in optimization \nc.                          basic knowledge in machine learning \n Content \nData-driven methods\, such as Gaussian processes\, make it possible to obtain models of unknown processes with uncertainty quantifications\, and have found widespread applications in recent years. This course gives an introduction to data-driven methods for robot control. \nThe course will start with a general introduction on the theory of Gaussian Process Regression [1]\, which will serve as a backbone for the remaining topics. \nThe theory will subsequently be exemplified through three use-cases: identification of inverse dynamics models of robotic manipulators [2]\, safety guarantees for uncertain dynamical systems [4]\, and learning of robot trajectories based on a given set of demonstrations [4]. \n[1] Wang\, Jie. “An intuitive tutorial to Gaussian processes regression.” Computing in Science & Engineering\, 2023. \n[2] J. S. de la Cruz\, W. Owen and D. Kulíc\, “Online learning of inverse dynamics via Gaussian Process Regression\,” 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems\, Vilamoura-Algarve\, Portugal\, 2012\, pp. 3583-3590\, doi: 10.1109/IROS.2012.6385817. \n[3] Y. Kim\, I. Iturrate\, J. Langaa and C. Sloth\, “Safe Robust Adaptive Control under Both Parametric and \nNon-Parametric Uncertainty”\, Advanced Robotics\, 2024. \n[2] M. Arduengo\, A. Colomé\, J. Lobo-Prat\, L. Sentis and Carme Torras\, “Gaussian-process-based robot learning from demonstration\,” J Ambient Intell Human Comput. 2023. https://doi-org.proxy1-bib.sdu.dk/10.1007/s12652-023-04551-7 \n Learning outcomes \nThe aim of the course is\, to give the student knowledge about: \n\nGaussian Process Regression and its application to robotics\n\nBe able to work with the following skills: \n\nQuantify the uncertainties of a dynamical system trajectories based on data\n\nAnd have the competences to: \n\n      Design controllers for uncertain dynamical systems using data-driven methods\n 	 \n\nTime of classes \nThe course will start in May 2024 and will have five sessions. \nThe course will last 5 days\, i.e.\, 40 hours. \n2.5 ECTS = 67.5 h (40 h teaching\, 15 h preparation\, 12.5 h hand-in)\n   \nMore information and registration:\n Via email to Christoffer Sloth (chsl@mmmi.sdu.dk) or Pia Mønster (pmkr@mmmi.sdu.dk).\n Deadline: 1 week before the classes start.\n   \nForm of instruction\n The teaching is a mixture of lectures and exercises\, where the students can apply the theory in practice.\n   \nExamination conditions\n Following is a prerequisite to attend the final project exam: \n\nParticipation in 80 % of the classes.\n\n Evaluation \nInternal examination with no co-examiner based on a submitted report with solutions to problems addressed during the classes. The assessment will be pass/fail.\n   \nPrice\n No charge \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/__trashed-9/
LOCATION:Campusvej 55\, Odense M
CATEGORIES:PhD Course
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