PhD Course Management

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In this workshop, we make the objectives of the PhD education explicit and equip students with strategies and tools to develop as independent scientists. In session 1, we discuss the skills and competences of a PhD – and their importance to society. In session 2, students present their research projects in small, cross-departmental groups and for each project discuss the opportunities for developing independence. Session 3 has a focus on the collaboration with supervisors and presents ways to negotiate roles and address progression during the education.

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To make the participants familiar with the most important medical databases, and enable them to perform qualified searches for relevant scholarly literature.  Furthermore, to make the participants aware of basic principles of research evaluation and different aspects related to research publication.

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This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific and academic writing process.

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The course is designed as a blended learning approach with a combination of out-of-class online learning and in-class face-to-face teaching. It is estimated to last over six weeks (4x4 hours in-class seminars, approx. and approx. 8 hours structured asynchronous online learning activities). The activities will consist of a mix of reading materials, watching videos, producing texts and models, participating in individual as well as group activities in-class and out-of-class, developing lesson plan and teaching portfolio as well as giving peer-feedback. To complete the course and receive ECTS credit and diploma it is mandatory to be active online and complete all activities (including peer-feedback and portfolio) and respect the activity deadlines.

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The course aims to

  • Provide theoretical background of advanced spatial modelling, analyses and visualization
  • Introduce participants to spatial programming
  • Give participants hands-on experience in advanced spatial analyses and programming with focus on health-related exercises

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A PhD is a time to submerge into interesting research and exciting new contexts, but it is also a time to tend to your future career. Your PhD is a step towards your next job regardless of your professional background and your thoughts on career direction. This session will aim at encouraging you to build career management skills during your PhD: strengthen your knowledge and understanding of how adding a career perspective to your PhD is beneficial both for your professional development as a researcher and for ensuring that you have the skills, knowledge and experience necessary for your next career step, whatever that is.

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The aim of the course is to introduce the student to the basic use of the software R. The course is designed to build up the basic skills in R necessary for attending to the PhD course Basic Statistical Analysis.

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To make the research year students familiar with the most important medical databases, and enable them to perform qualified searches for relevant scholarly literature. Participants will be introduced to systematic literature searching as well as citation searching and reference management.

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The aim of this course is to ensure participants are able to apply the Three Rs (reduce, replace, refine) effectively in the design of procedures and projects and make appropriate ethical and scientific judgments. The course is obligatory for persons who wish to achieve a personal license to independently plan, implement and take responsibility for the design and performance of animal experimentation within the European Union according to the EU Directive 2010/63/EU Article 23.2 and the Danish executive order 12 of 07/01/2016, §56.

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The aim of this course is to: 1) Equip students with the tools they need to approach and deliver a high quality, high impact scientific paper, proposal or poster. 2) Give students a space for immediate and direct feedback to progress more rapidly with their active or developing manuscripts or proposals

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The aim of this course is to take a practitioners approach to project management focusing on both technical and sociocultural skills.

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The aim of the course is to introduce the PhD student to basic notions of statistical analysis and give an idea of a typical statistical modelling process.

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The aim of the course is to give a practical and theoretical introduction to immunoassays with focus on quantitative assays (ELISA, TRIFMA). The course will give the participants skills to work with quantitative immunoassays in the laboratory and to troubleshoot in relation the daily routine work.

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At this course you will practice a number of writing tools that will make your daily writing practice more efficient.

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The purpose of the course is to give participants in-depth knowledge of clinimetric testing of questionnaires and how to interpret relevant statistical output.

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The aim of this course is to impart knowledge about and give course participants an introduction to academic text production in English, applying textual and discourse strategies and methodologies in accordance with the current conventions of written academic English in health sciences.

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The aim of the course is to provide participants basic understanding of the programming environment MATLAB. Enable participants to use built-in MATLAB functions and create own scripts and functions for data evaluation and visualization.

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The aim of this course is to train the students’ general and disciplinary writing ability to enhance successful disciplinary writing in conformity with contextual/situational, discoursal and genre- and text-type conventions and requirements of written academic English in health sciences.

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To give the participants an introduction to Analysis of Variance with focus on repeated measures in experimental studies, and to enable the participants to choose a relevant statistical analysis of own data.

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The aim of the course is to o avoid misuse and misinterpretations of statistical significance testing.

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This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific and academic writing process.

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 Introduction event for all newly enrolled PhD students at Graduate School of Technical Sciences, Aarhus University.

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To achieve knowledge on data documentation, basic statistical tests and the assumptions for performing these tests.

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This peer-feedback course is only available for research year students. The course is focused on academic and personal development throughout the research year. Students will be put in groups of 4-5 students for the entire year. The groups will meet 4 times, and in the meetings each student will give a short presentation (5-10 minutes) to the group, followed by 20 minutes for feedback. Each group will also have a fixed mentor for the year, who will be responsible for guiding the process during the meetings.

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To support PhD students in their career decision-making process by increasing their career awareness, and to prepare them for the transition between academia and industry/public sector jobs.

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Participants will learn about key Danish national registers and how to use them for research purposes, through a combination of lectures, short research presentations with examples, discussions and exercises. This course will provide participants the necessary knowledge and skills to start their own research project based on national registers and cohorts.

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The course aims to provide students with the skills necessary to critically use the qualitative software programme NVivo and to train the students in using NVivo to organise and analyse different types of qualitative data.

 

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Epidemiologic measures of occurrence and association, study designs - including macro-epidemiological, cross-sectional, case-control and cohort studies as well as experimental, randomized controlled trials - interpretation and inference, including random error, selection and information bias, confounding and effect modification. A specific session will deal with causation. Please see time schedule and teaching objectives for details.

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Collecting, analyzing, storing and sharing data are central activities in research. Research Data Management (RDM) and FAIR (Findability, Accessibility, Interoperability, Reusability) principles are thus becoming increasingly important, and researchers are often required by institutions and funders to prepare a data management plan. Open Access (OA) publishing is another aspect related to sharing research output, which implies that scholarly publications are distributed online, free of any access barriers.

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By the end of the course, the PhD student will:

  • Be familiar with the Danish Code of Conduct for Research Integrity as well as Aarhus University guidelines and Health standards of Responsible Conduct of Research
  • Be able to understand and discuss principles of research integrity and responsible conduct of research
  • Be able to identify, analyse and discuss cases of scientific misconduct and questionable research practices in the grey zone between misconduct and poor science
  • Know where to seek advice concerning responsible conduct of research

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A welcome event for all newly enrolled PhD students to the PhD programme to give  them the opportunity to meet and interact with fellow PhD students and AU representatives from fields relevant during the PhD programme.

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Kurset er en overbygning på det tre dages varende grundmodul i forskertræning afholdt af Århus Universitet, og henvender sig til de læger under uddannelse, hvis speciale ikke har et selvstændigt overbygningskursus. 

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There are many challenges to capturing the complexity of exposures in an individual across the lifetime and their potential health effects. Traditionally, environmental health studies have focused on assessing risks related to a single exposure at a time, yet in reality we are constantly exposed to multiple exposures at the same time. To advance environmental health research and positively impact human health through recommendations and policy, we need to incorporate omics data that capture all chemical species detectable in human plasma and related molecular changes over the life course. The exposome offers this framework and can be viewed as the environmental complement of the genome.

This course integrates the principle concepts of exposomics and the untargeted approaches of measuring exogenous and endogenous chemical exposures and molecular changes on an omic scale. We will step through the tools and techniques currently available to analyze the exposome. We will integrate seminar lectures with group work and presentations to put concepts into practice. Emphasis will be given to leveraging existing resources from ongoing studies and initiating new investigations.

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The onboarding programme will introduce different work tools all relating to the process of initiating and doing a PhD project in the best way possible. These will be introduced through peer-mentoring groups and workshops with different topics. By participating in the onboarding programme the PhD students will be offered an insight into handling ups and downs during their PhD, and how to develop as a young scientist. The onboarding programme will also give the PhD students an opportunity to meet fellow PhD students and expand their network – both socially and academically. Read more here.

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This course aims to impart knowledge about and give participants an introduction to and practical experience using artificial intelligence (AI) tools to enhance their scientific and academic writing process.

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To create a framework for integrating project management tools into work habits for Ph.D. students to help them stay on track or get back on track in the second half of the PhD process.  The content includes time to reflect on bottlenecks and scheduling needs related to completing your Ph.D. project on time.  In addition, you will be introduced to risk analysis tools, and Kanban boards.

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The course will provide didactic and plenum discussions on cancer diseases and research. The theoretical lectures will include insight into the disease, methodology for research, progression to clinical trials, and common errors that hamper project development. The course will have a strong focus on the progression of a project from basic research to clinical application. Furthermore, students are asked to present their projects, including a critical perspective and applied new possibilities for the projects to reach a higher impact of their work.

 

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The aim of this course is to introduce the concept of patient and public involvement in health research and acquire participants a science- and theory-based understanding of patient and public involvement in health research. The course will increase the participants’ ability to identify and increase the value of patient and public involvement in health research by suggesting how patient and public involvement in health research could optimally be a part of their own study and which implications would be important for practice.

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The course focus is on image diagnostic methods and their potential for research and clinical investigation of the human body/musculoskeletal system including baseline knowledge on their advantages/limitations and risks (radiation physics, protection and doses/risks). Methods included are: X-ray, DXA, Radiostereometry, CT, Cone Beam CT, HRpQCT, mCT, Dynamic NaF PET, MRI, Musculoskeletal modeling (AnyBody Modeling System), 3D printing and surgical guides, and Augmented reality. 

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A PhD is a time to submerge into interesting research and exciting new contexts, but it is also a time to tend to your future career. Your PhD is a step towards your next job regardless of your professional background and your thoughts on career direction. This session will aim at encouraging you to build career management skills during your PhD: strengthen your knowledge and understanding of how adding a career perspective to your PhD is beneficial both for your professional development as a researcher and for ensuring that you have the skills, knowledge and experience necessary for your next career step.

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Welcome to the PhD Course Management

Please make sure to keep your contact email updated so we can send you course information.

For more information regarding specific faculty course rules and regulations, please visit the following websites:

Graduate School, Arts - PhD Course information

Graduate School Health – PhD Course information

Graduate School of Natural Sciences – PhD Course information

Scientific courses at Graduate School of Natural Sciences

Graduate School of Technical Sciences – PhD Course information

Scientific courses at Graduate School of Technical Sciences

Best regards, 

PhD Administration

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