PhD Course Management

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The course provides detailed knowledge on flow cytometry, with a thorough review of the theoretical foundation necessary for performing state-of-the-art flow cytometry experiments, and includes extensive practical hands-on data analysis exercises covering the most important topics and pitfalls. Thus, the course provides the participant with a broad understanding of how to design multicolour flow cytometry experiments, how to handle sample material, and how to analyse and present flow cytometry data for publication.

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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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The overall aim is to give the participants understanding of cardiovascular physiology and methods of assessment. The course will provide the participants with the knowledge to choose the optimal methods for their individual research projects based on the methods’ strengths and weaknesses.

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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:

  1. Provide students with the state-of-the-art knowledge on genome engineering and CRISPR gene editing technology
  2. Introduce the different types of CRISPR gene editing tools (e.g., base editing, prime editing) and their applications
  3. Provide trainings on CRISPR designing with high on-target efficiency and low off-target
  4. Provide trainings on design CRISPR and donor vectors for gene knockin, tagging
  5. Introduce CRISPR data science, CRISPR AI, and high-throughput CRISPR computing
  6. Provide trainings on analysing and understanding CRISPR editing data with TIDE, ICE and NGS
  7. Provide theocratical trainings and education on CRISPR gene therapy
  8. Introducing state-of-the-art methods for CRISPR delivery
  9. Provide laboratory trainings on CRISPR-mediated gene knockout and knockin in cultured cell lines.
  10. Prepare PhD students with essential knowledge, tools and skills for their gene editing projects

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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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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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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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The course covers the principles of Good Clinical Practice (GCP) and the roles of Sponsor, Investigator, Monitor, the ethics committee and the regulatory authorities.

Focus will be on the practical aspects on how to comply with the principles of Good Clinical Practice (GCP) and requirements in the national regulations in Denmark for Clinical trials with medicinal products.

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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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The aim is to introduce, discuss and apply family-focused approaches, methods, and evaluations in health science 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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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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To provide students with an overview on how to take a research idea through to implementing, analysing, and interpreting an epidemiologic study using the Danish Clinical Cancer Databases, and Denmark’s network of medical and population-based registries. Each concept will be introduced in a lecture. Through a combination of exercises and computer labs, students will be provided with guidance on implementing, analysing and interpreting studies using data from the clinical cancer databases. Students are not required to complete an exam at the end of the course. 

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Provide an overview of the different aspects of conducting clinical research

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The aim of the course is to ensure that the participants can convey and handle responsible research communication of their own PhD project. Through different media channels and via different presentation techniques, the participants will be able to explain and present complex research in an engaging and understandable way to an audience whether it be the general public, journalists, patients, students in a classroom or a foundation’s review committee.

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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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In the workshop, the participants will clarify the central requirements of their doctoral situation and recognise in which areas there is still catching up to do.

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This course enables a qualified debate about the relevance and applicability of current knowledge on stress and resilience to advance mental health and clinical practice. 

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

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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 aim is to introduce to the conduct of a qualitative content analysis, and enable the participants to design and plan a qualitative content analysis. The participants will be able to apply qualitative content analysis, to make consistent and well-informed analytical choices, and to reflect on relevant methodological issues related to their study design and plan of conduct.

The course is relevant both for students who are planning to conduct a qualitative study or literature review, and for students who will use the qualitative content analysis to analyze their conducted material (e.g., interviews, field notes, transcripts, documents, articles).

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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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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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To focus on knowledge that is critical for success in an academic research career. With a point of departure in the PhD students’ present and future career goals, this course explores key building blocks of successful academic research careers.

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In this module, AU Library will introduce you to the task of working with data and publications, both your own and that of others: How to find data and publications, manage them, and what to be aware of, when you want to publish your results, including copyright and Open Access.

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 Introduction event for all newly enrolled PhD students at Natural Sciences, Aarhus University.

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This PhD course aims to provide a comprehensive introduction to the principles, developments, and applications of single-cell and spatial OMICS technologies. Students will gain fundamental knowledge of sequencing and profiling methods used to study genomics, epigenomics, transcriptomics, metabolomics, and proteomics at both single-cell and spatially resolved levels.

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The course aims to provide the background for critical reading and interpretation of epidemiological research articles.

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The course aims to provide the basic tools to use Mixed Models, including Gaussian Linear Mixed Models, Models for Repeated Measures, Generalised Linear Mixed Models and simple Multivariate Generalised Linear Mixed Models.

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To introduce advanced optical techniques for in vivo imaging and how these can be applied in research projects.

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This course aims to give PhD students a greater understanding of the R language for them to produce more clean, sophisticated and efficient R code, and also make them adopt better practices and learn more about packages and tools that will simplify their life when coding in R and doing some data analysis and visualization.

Note that this is NOT a Statistics course.

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As a part of their teaching responsibilities, PhD-students sometimes act as co-supervisors for undergraduate students’ bachelor projects, written assignments, master thesis, or research year assignments. In doing so, the PhD-students play an important role as a near-peer-supervisor guiding the students in their learning. This course aims to prepare PhD-students for their role as co-supervisors on undergraduate students’ assignments and/or learning processes. The course is relevant for all PhD students who wish to improve the quality of their supervision of undergraduate students.

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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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