• Description: This course will cover familiar epidemiological concepts like bias, confounding, and other systematic errors, but will go into more details with a focus on how and why the validity of results might be endangered. The use of Directed Acyclic Graphs for identifying sets of covariates necessary for robust adjustment of models will be introduced. The identification and interpretation of interaction/effect modification will be covered with the aim of describing how subgroups might behave differently. Finally, the course will cover more recent developments in epidemiology, by introducing causal inference from observational studies using counterfactual models and propensity scores, mediation analyses and the use of instrumental variables. The course will include lectures and group work based on selected papers and problems related to the projects of the participants.

    Literature: Selected papers and book chapters.

    Evaluation: Active participation and presentation from group work.

    Prerequisites: Skills corresponding to basic epidemiology and basic statistical courses.

  • Organizer: Associate professor Henrik Bøggild, e-mail: boggild@hst.aau.dk

  • Lecturers: Associate professor Henrik Bøggild, professor Kirsten Fonager, professor Søren Paaske Johnsen and invited lectures Public Health and Epidemiology Group, Health Science and Technology, Aalborg University, Center for Clinical Health Service Research, Department of Social Medicine and Unit of Clinical Biostatistics, Aalborg University Hospital

  • ECTS: 2,4

  • Time: November 2021

  • Place: TBA

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 20

  • Deadline:
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
  • Description:

    This course deals with basic principles of epidemiology and will prepare the students for further courses in advanced epidemiology. The course will consist of lectures and group-work based on scientific papers.


    The main themes are:

    • Descriptive studies
    • Measures of associations
    • Observational design, including cross-sectional studies, cohort studies, case control studies
    • Experimental studies (randomized controlled trials)
    • Sources of information for epidemiological studies
    • Issues of precision
    • Issues of validity, including bias and confounding
    • Applications of epidemiology in different areas, including clinical epidemiology


  • Organizer: Kirsten Fonager, Ph.D, professor, Henrik Bøggild, Ph.D, associate professor

  • Lecturers: Kirsten Fonager, Ph.D, professor, Henrik Bøggild, Ph.D, associate professor and others

  • ECTS: 3,2

  • Time: October 7-8 and 14-15 2021

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 30

  • Deadline: September 16

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description: The course aims to provide a comprehensive review of clinical research with emphasis on how to design and how to perform a clinical study and thus give the participant the necessary tools to perform clinical trials. The course contains a comprehensive review on how to plan and perform clinical trials involving humans. Different designs (the randomized controlled trial and other designs including more specialized designs) are reviewed and the planning of a clinical trial is presented. Power calculations are reviewed in detail in order to provide the participant with the necessary tools to give an estimate of the number of subjects needed for a clinical trial. Methods (biochemical methods, diagnostic tests, reliability, coefficient of variation etc.) are reviewed and concepts such as evidence based medicine, collaboration with the medical industry, the legal aspects of a clinical trial (how to write a contract, legal obligations etc.), how to review a paper, practical aspects of biobanks, and how to perform meta-analyses are covered. Emphasis is put on practical exercises related to the topics mentioned above along with lectures.

  • Organizer: Professor, consultant, PhD DrMedSc Peter Vestergaard, e-mail: pev@dcm.aau.dk 

  • Lecturers: Peter Vestergaard, Louise Bornebusch Lund, Bo Kristensen Jessen, Louise Hansen, Britt Laugesen, Søren Risom Kristensen, Henrik Krarup, Jesper Karmisholt, Bodil Steen Rasmussen

  • ECTS: 3,2

  • Time: 6-9 December 2021

  • Place: TBA

  • Zip code: 9220

  • City: Aalborg East

  • Number of seats: 30

  • Deadline: 16 November 2021

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description:

    This course will provide the participants with hands-on experience in creating and handling data from questionnaires, registers and other sources, and to document the data management process and analyses using the principles of an audit trail.

    This is in accordance with the Code of Conduct/UVVU recommendations and with the Danish Data Protection Agency regulations.

    The course provides an overview of the audit trail and hands on experience in creating a dataset ready for statistical analyses with the accompanying documentation including labelling, double entry, error corrections, data modification and analyses producing tables and figures in a way, that is reproducible.

    We will use REDCap, for those not having access to that, EpiData will be a secondary possibility. SurveyXact can also be used for producing survey data in accordance with the principles laid out.

    Regardless of the software used for statistical analyses (for instance SPSS, STATA, SAS or R) participants will learn how to document the analyses in command files. It is recommended that participants have knowledge on their statistical program in order to gain most from this.

    Participants work on data documentation of own or provided data between the two lessons.

    Before the course a questionnaire about the use of and experience with various statistical software will be distributed.

    Literature: Provided book and regulations.

    Evaluation: Active participation and created data documentation.



  • Organizer: Associate Professor Henrik Bøggild, e-mail: boggild@hst.aau.dk

  • Lecturers: Associate Professor Henrik Bøggild, Public Health and Epidemiology Group, Health Science and Technology, Aalborg University

  • ECTS: 1,5

  • Time: 17 and 24 September 2021

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 30

  • Deadline: 27 August 2021

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.


  • Description:

    Multilevel data emerges in many types of quantitative epidemiology studies. Whether we are using a randomized block design in a clinical trial, applying generalizability theory to performance measures, investigating variability across regions and municipalities, handling subject recurrence, conducting a network meta-analysis or simply trying to avoid overfitting.

    In this course we discuss the following methodologies and when to apply them in multilevel analyses:

    ·       Cluster-robust variance and clustered bootstrap

    ·       Mixed effects modelling (crossed, nested and combined)

    ·       Median effects and intraclass correlation coefficient

    ·       Inverse probability of treatment weights incl. balance diagnostics.

    The course is mainly concerned with interpretation of research results.

    Literature: Course material will be sent out during the course

    Prerequisites: Basic Statistics and basic programming abilities with Stata or R, all participants must bring a laptop with either Stata or R installed. R is recommended for the majority of the assignments.

    Evaluation: Assignment with oral presentation in groups of 2-4 participants



  • Organizer: Jan Brink Valentin, jvalentin@dcm.aau.dk

  • Lecturers: Jan Brink Valentin, jvalentin@dcm.aau.dk

  • ECTS: 2,5

  • Time: 14th, 15th and 16th of September 2021 from 08.30 to 16.00

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 30

  • Deadline: 24 August

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.


  • Description:

    While most medical studies aim to explain some phenomenon, a significant proportion does not have this as a primary goal. These studies instead aim to predict a certain event or measure as accurately as possible given a number of predictors. Although explaining and predicting are two separate goals, they are often interchanged in medical studies. More importantly, the statistical approaches used for these two types of data analyses are not the same. The course covers the following topics:

    1. The basic differences between explanatory and predictive studies.
    2. Model estimation: variable selection, variable predictive power and penalisation
    3. Model Performance: N-fold cross validation, geographical and temporal validation, external validation.
    4. Model validity: Calibration and calibration slope, receiver operating characteristic (ROC) curve incl. area under the curve (AUC), coefficient of determination and prediction intervals
    5. Examples from the scientific literature

    Upon completion of the course, the student will be able to distinguish between predictive and explanatory data analyses, as well as understand the basic statistical tools used in predictive studies.

    Literature:

    Moons K, Royston P, Vergouwe Y, Grobbee D, Altman D. Prognosis and prognostic research: what, why and how? BMJ2008;b375.

    Ewout W. Steyerberg, Yvonne Vergouwe; Towards better clinical prediction models: seven steps for development and an ABCD for validation, European Heart Journal, Volume 35, Issue 29, 1 August 2014, Pages 1925–1931, https://doi.org/10.1093/eurheartj/ehu207

    Prerequisites: Basic Statistics and basic programming abilities with Stata or R, all participants must bring a laptop with either Stata or R installed

    Evaluation: Assignment with oral presentation in groups of 2-4 participants


  • Organizer: Lasse Hjort Jakobsen (lasse.j@rn.dk), Jan Brink Valentin (jvalentin@dcm.aau.dk)

  • Lecturers: Lasse Hjort Jakobsen, Jan Brink Valentin, Simon Grøntved

  • ECTS: 3,5

  • Time: May 31st, June 1st, 3rd and 4th 2021 from 08.30 to 16.00

  • Place: Niels Jernes Vej 14, room 3-119. On June 4th in room 4-111

  • Zip code: 9220

  • City: Aalborg East

  • Number of seats: 40

  • Deadline: 8 June 2021

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description:

    The objective of this course is to give the participants an introduction to an important tool in biomedical research – statistical software, Stata. Based on real data from medical research projects the intent is to give the participants an insight into the process of transforming raw data into output that is suitable for a publication. During the course the participants will be introduced to the following possibilities in Stata:

    1. How to load data.

    2. How to prepare data for analysis.

    3. How to run analysis.

    4. How to manage output.

    5. How to present results.

    6. How to learn more.


    The course will consist of both plenum presentations and hands-on exercises.

    Prerequisites

    It is recommended to bring a laptop with Stata installed – preferably the latest version.



  • Organizer: Niels Henrik Bruun, nbru@rn.dk

  • Lecturers: Niels Henrik Bruun, nbru@rn.dk

  • ECTS: 0,8

  • Time: 8 September 2021

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 28

  • Deadline: 18 August

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description: Essentially all statistical problems can be formulated as regression problems: the problem of quantifying the relationship between a dependent variable and one or more independent variables. Surprisingly many statistical problems encountered in clinical practice can be succesfully handled with a small set of "core regression techniques", alongside an understanding of the rationale and limitations of statistical regression in general. The present course is a case-based introduction to these core regression techniques, with an emphasis on common features rather than differences. Upon completion of the course, the student will be able to perform basic regression analyses in a suitable statistical software program. The student will also obtain a broad foundation for learning and applying other and more advanced regression techniques.
    Topics covered will include the following:
    • From research question to regression analysis
    • Simple linear regression
    • The t-test
    • Multivariable regression (adjustment)
    • Analysis of variance
    • Regression in small samples
    Software
    The course includes computer practical exercises. Examples will be provided in Stata syntax but other relevant software packages can be used for exercises.
    Evaluation
    Evaluation of the course will be based on active participation in the course including a practical exercise which is to be handed in after the course.

  • Organizer: Søren Lundbye-Christensen og Martin Nygård Johansen

  • Lecturers: Søren Lundbye-Christensen og Martin Nygård Johansen

  • ECTS: 2,4

  • Time: 19. 27. and 31 May 2021

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 20

  • Deadline: 28 April

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description:

    Clinical data science can be defined as the scientific field, which turns healthcare data into clinically useful applications. This course will introduce the disciplines involved in the full value chain of clinical data science, covering the transformation of data to model and to applications, with an aim of giving an overview and understanding of the processes, rather than how to perform them. The course is organized into three major themes:

    1)    Data sources: The first part of the course covers the management and collection of data from both public sources, national registries or trough case report forms designed for a study. We will introduce both how to access data, how to handle privacy concerns (GDPR) and how to make your own data useable for others (FAIR principles).

    2)    Modelling: The second part of the course teaches how to transform the collected data from possibly multiple sources to input for a predictive model, and how to train and validate a model using techniques such as classification, regression, or clustering.

    3)    From model to clinic: The final part of the course deals with turning a validated model into a clinical decision support system to strengthen operational excellence in value-based health care. How do we ensure that data is available in real time? What legal barriers or ethical issues are involved when a medical decision is guided by artificial intelligence?

    Prerequisites:  Experience with collecting and analyzing health care data.

    Literature:  Kubben, P., Dumontier, M., Dekker, A. (editors) Fundamentals of Clinical Data Science. Springer Open, 2019. Available online at: link

    Evaluation: The participant must present a mock-up of a decision support tool, covering a clinical problem related to their own area of research.


  • Organizer: Rasmus Froberg Brøndum, Associate Professor, rfb@rn.dk                   Martin Bøgsted, Professor, martin.boegsted@rn.dk

  • Lecturers: Charles Vesteghem, Lasse Hjort Jacobsen, other experts

  • ECTS: 3

  • Time: 22-24 June 2021

  • Place: Auditorium B, Forskningens Hus, Sdr. Skovvej 15

  • Zip code: 9000

  • City: Aalborg

  • Number of seats: 30

  • Deadline: 1 June 2021

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

  • Description:

    One of modern biology’s biggest surprises was the finding that the human genome contains only about 20,000 protein-coding genes, comprising less than 2% of the genome sequence. However, recent data imply that the human genome is pervasively transcribed and encodes tens of thousands of non-protein coding RNAs (ncRNAs) that play critical regulatory roles in numerous biological processes. These ncRNAs include over 2,300 microRNAs (miRNAs), a set of structural RNAs [such as ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), and small nuclear RNAs (snRNAs)], and at least 50,000 long noncoding RNAs (lncRNAs). An improved understanding of basic RNA biology and the complexity of the human transcriptome has triggered a corresponding revolution in development of RNA-based therapies, which hold promise for the treatment of a wide range of life-threatening diseases. This is highlighted by the recent FDA approvals of three RNA medicines: (i) the antisense oligonucleotide (ASO)-based drugs eteplirsen for treatment of Duchenne muscular dystrophy and (ii) nusinersen for treatment of the neurodegenerative disease spinal muscular atrophy, respectively, and (iii) the siRNA drug patisiran for the treatment of hereditary transthyretin amyloidosis with polyneuropathy. Notably, RNA drugs can be designed to target essentially any RNA transcript encoded by the genome and can thus target a large part of the currently undruggable genome.

    This PhD course will provide the participants with an overview of ncRNA biology and development of RNA-targeted therapeutics, and consists of a series of research seminars and laboratory exercises. The seminars will cover key topics in the rapidly expanding field of RNA research from ncRNA biology, high-throughput RNA sequencing (RNA-seq) methods and bioinformatics/computational analysis of RNA-seq data to the emerging roles of ncRNAs in human disease and development of RNA-based medicines. Each seminar will be followed by a scientific discussion of the participating PhD students with the lecturer. As preparation, two scientific papers selected by the lecturer have to be read prior to the PhD course. The laboratory exercises are designed to provide hands-on experience with key methods and tools used in ncRNA research and discovery of RNA-targeted therapeutics.

    Literature:

    1. Khvorova A & Watts JK. The chemical evolution of oligonucleotide therapies of clinical utility. Nat. Biotechnol. 35: 238–248 (2017).
    2. Lim KR, Maruyama R & Yokota T. Eteplirsen in the treatment of Duchenne muscular dystrophy. Drug Des Devel Ther. 11: 533-545 (2017).
    3. Corey, DR. 2017. Nusinersen, an antisense oligonucleotide drug for spinal muscular atrophy. Nat Neurosci. 20: 497–499 (2017).
    4. Setten RL, Rossi JJ & Han SP. The current state and future directions of RNAi-based therapeutics. Nat Rev Drug Discov. 18: 421-446 (2019).

    Prerequisites: PhD students in biomedical research or molecular biology with an interest in ncRNA biology in human health and disease and discovery and development of RNA-targeted therapeutics should apply.

    Evaluation: Participants who have engaged actively in all parts of the course and completed all lab exercises satisfactorily will be awarded a certificate of completion at the end of the PhD course. The workload corresponds to 5 ECTS points, and includes one week of preparation prior to the course (2 articles for each lecture that should be read in advance).


  • Organizer:
    Sakari Kauppinen, Professor and Director, Center for RNA Medicine, Dept of Clinical Medicine, e-mail:
    ska@dcm.aau.dk, website: www.rna-medicine.dk

  • Lecturers:

    Sakari Kauppinen, Professor and Director, Center for RNA Medicine
    Mogens Vyberg, Professor of Clinical Pathology, Center for RNA Medicine                         
    Shizuka Uchida, Professor (WSR) in Bioinformatics and RNA Computational Biology, Center for RNA Medicine
    Marianne Løvendorf, Assistant Professor, Center for RNA Medicine
    Anja Holm, Assistant Professor, Center for RNA Medicine
    Kasper Thystrup, PhD Student, Center for RNA Medicine


    • ECTS: 5

    • Time: 8-12 November 2021

    • Place: Center for RNA Medicine, Dept of Clinical Medicine, Frederikskaj 10B, AAU Campus Copenhagen

    • Zip code: DK-2450 Copenhagen SV

    • City: Copenhagen

    • Number of seats: 16

    • Deadline: 18 October 2021

    Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.