Welcome to Situational analysis - how to capture complexity (2017)
Description:

Situational analysis is a method developed by Adele Clarke, to give researchers practical mapping tools for designing qualitative research projects and conducting analysis of qualitative empirical material. The methodology is particular useful for multi-sited ethnographic projects, research projects including both human and non-human actors and multi forms of empirical material. 

  The course will be concentrated on introducing the mapping methodologies presented in Adele Clarkes Situational Analysis – grounded theory after the postmodern turn (2005). The aim of the course it to give the theoretical and methodological background for mapping research projects, and is meant to support the Ph.D. students work with their own projects.

Since situational analysis is a theory/method package, emphasis in the course is especially on introducing how the Situational Analysis and its mapping tools are developed. The theoretical basis being feminist developments  of situated knowledge’s, Michel Foucault’s discourse analysis, and Anselm Strauss Symbolic Interactionism and social world/arena theory. The methodological approach will concentrate on the grounded theory after the post-modern turn as Clarke is unfolding in the book.

During the course students will have to work with Clarke’s methodology by applying SA mapping approaches in relation to their own project design and/or empirical data. This is meant to support the process of the reflections in the Ph.D. projects.

More information on the detailed course program will be announced later.

Organizer: Mette W. Hansen

Lecturers:
Responsible: Mette W. Hansen. Others will be announced.

ECTS: 5

Time: November 2017

Place: Aalborg University, Copenhagen - room to be announced City: 2450 Copenhagen

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 5,000 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 three 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.

Welcome to Design and Analysis of Experiments

Description: After a short survey of basic statistical concepts such as estimation, significance tests and confidence intervals, an introduction will be given to the analysis of designed experiments, including analysis of variance and factorial designs. The course will also cover multiple and polynomial regression. The course will be accompanied by an introduction to a dedicated statistical software package (R, see more at http://www.r-project.org).

Prerequisites: The course assumes basic knowledge about mathematics and probability theory as obtained through the engineering courses at Aalborg University. Some knowledge about basic statistics, such as one sample estimation and test of hypotheses, will be desirable.

Organizer: Associate Professor Esben Høg, email: esben@math.aau.dk and Associate Professor Torben Tvedebrink, email: tvede@math.aau.dk

Lecturers: Esben Høg and Torben Tvedebrink

ECTS: 4

Textbook: Douglas C. Montgomery. Design and Analysis of Experiments, 8th ed. Wiley, 2012

Time: 13-14, 20-21 and 27-28 September + 4- 5, 11-12 and 18-19 October 2017

Evaluation:

  • Active attendance in at least 9 out of 12 lectures
  • Hand in a statistical analysis done in the last two lectures (needs to be passed

Place:

Zip code: 9220

City: Aalborg

Number of seats: 40

Deadline: 23 August, 2016

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 5,000 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 three 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.

Welcome to Qualitative Methods for User Research in Science, Engineering and Medicine
Description: This course will outline theory and practiæ of qualitative research methods within science, engineering, health, foodscape studies and medicine. A variety of methodological approaches will be introduced. There will be a special focus within video observation and ethnographic studies. Qualitative research has expanded within natural science, typically in a mix method srategy, and aften with use of same kind of interviews and/or video observation. The complex interaction of usersin different contexts is found in a broad range of fields in modern lifeandis studiedin a number of different scientific fields. Qualitalive research methods are important tools for approaching the understanding and interpretation of these phenomena. The course will take both a theoretical and a practical approach. The theoretical approach by relevant theories and methods for conceptualizing the design, data collection, data analysis and reporting. The practical approach by some hands-on within video observation and data analysis.

Learning objectives: The course will provide knowledge within new methods and the underlying theories such as a general understanding of interviews, video-ethnographic methods, probes, self-provided photo safaris, customer journey, interactive video footage sessions, card sorting, projective techniques, ethical considerations, data analysis with use of software. The participants will be given skilis and competences (understanding, applied and able to analyze) relevant qualitative research methods, both in general and linked to own current project.

Teaching methods:

Lecetures with presentation of different methodological overviews. 60 %

workshop where participants will work in groups e.g. with using video observational methods. The groups set-up own theoretical focus. 40%

Criteria for assessment:

l. Participation all three days

2. Individual paper (uploaded in Moodle) or e-mail

3. Presentations linked to your current PhD project. The presentation must somehow have a focus within qualitative/mixed methods research. The focus can be within empirical data, ethnical issues, theoretical or even more abstract methodolocial questions. The duration of the presentation must not be more than 8 minutes. Your presentation should include a specific quesion/problem you would like for discussion/advice.

The exam ends with pass or no-pass.

Key litterature:

  • Bjørner, T. ed. (2015). Qualitative Methods for Consumer Research: The Value of the Qualitative Approach in Theory and Practice. Copenhagen: Hans Reitzels Forlag. Pp. 11-112.
  • Sarah Pink (2007): Doing Visual Ethnography, 2nd. Edition: Sage.
  • Raymond Hold (1958): Roles in Sociological Field Observations. Social Forces 36(3), pp. 217-223: Oxford University Press. Online, Moodle, Course, Day 1
  • Ylirisku & Buur, J. (2007): Designing with Video. Focusing the usercentred design process. Springer. Onlinge, Moodle, Course Day 1
  • Derry, S.J, Edt. (2007). Guidelines for Video Research in Education: University of Chicago

Organizer: Associate Professor Thomas Bjørner, email: tbj@create.aau.dk

Lecturers: Associate Professor Thomas Bjørner (AAU), Professor Bent Egberg Mikkelsen (AAU), Lise Justesen (Metropol), Lene Heiselberg (DR)

ECTS: 4 (with paper), 3 (without paper)

Time: 24-26 October 2017

Place:

Zip code:

City:

Number of seats: 25

Deadline: 3 October 2017

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 5,000 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 three 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.

Welcome to Biostatistics II

Description: This course on biostatistics will focus on the complexity of data collected in biomedical research. Therefore, the course will focus on topics like sample size estimation, meta-analysis and multi-factorial methods. This course will consist of two parts: (i) a review of some well-known and widely used parametric and non-parametric methods and discussions of basic designs of experimental studies, and (ii) a practical part where the focus is on applying the methods to relevant and realistic data sets collected from medical and biomedical research.

The tentative course program is:

  • Power analysis and sample size estimation
  • Meta-analysis and systematic reviews
  • Multifactorial ANOVA
  • Repeated measures ANOVA
  • Multiple and non-linear regression
  • Survival Analysis

Literature: Selected papers and book chapters will be announced to the participants shortly before the course.

Prerequisites: Biostatistics I or similar knowledge on biostatistics

Evaluation: Evaluation of the course will be based on written reports of selected exercises.

Organizer: Associate Professor Carsten Dahl Mørch, email: cdahl@hst.aau.dk

Lecturers:

ECTS: 4.5

Time: 6,10,13,17,20,24. November and 8 December 2017

Place:

Zip code: 9220

City: Aalborg

Number of seats: 35

Deadline: 16 October 2017

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 5,000 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 three 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.

Welcome to Bayesian Statistics, Simulation and Software – with a view to Application Examples

Description: During the last decades Bayesian statistics has gained enormous popularity as an elegant and powerful computational tool to perform statistical analysis in complex stochastic models as applied in engineering, science and medicine. Bayesian statistics offers an alternative approach to traditional data analysis by including prior knowledge about the model parameters in form of a prior distribution. Using Bayes formula the prior distribution is updated from the posterior distribution by incorporating the observed data by means of the likelihood. Subsequently statistical inference about the unknown model parameters is derived from the posterior distribution. However the posterior distribution is often intractable due to high-dimensional complex integrals implying that approximate stochastic simulation techniques such as Markov Chain Monte Carlo (MCMC) methods become crucial. This course reviews the basics ideas behind Bayesian statistics and Markov chain Monte Carlo (MCMC) methods. Background on Markov chains will be provided and subjects such as Metropolis and Metropolis-Hastings algorithms, Gibbs sampling and output analysis will be discussed. Furthermore, graphical models will be introduced as a convenient tool to model complex dependency structures within a stochastic model. The theory will be demonstrated through different examples of applications and exercises, partly based on the software packages R, BUGS and JAGS.

Prerequisites: The course is accessible to those new to these subjects; however, a basic knowledge of statistics and probability theory as obtained through engineering studies at Aalborg University is expected.

Frequently asked questions:

  • Q: If I participate in the course, can you then help me analyze a dataset that I work with as part of my ph.d. project.
  • A: No, I am afraid that this is not possible
  • Q: I would like to participate in the course, but during a part of the course period I can not be present. Is it possible to follow to course via Skype or similar?
  • A: No, I am afraid that this is not possible
  • Q: I am not a ph.d. student, but I would like to participate in the course anyway. Is that possible?
  • A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk
  • Q: I realize that I am late for enrollment, but I would really like to participate. Is it possible.
  • A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk

Organizer: Professor Jesper Møller, jm@math.aau.dk

Lecturers:

ECTS: 4

Time: 20-22 and 27-29 November 2017

Place:

Zip code: 9220

City: Aalborg

Number of seats: 40

Deadline: 30 October 2017

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 5,000 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 three 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.

Welcome to Advanced Mathematics for PhD Candidates

 

Description: The aim of this course is to give the participants an idea of how the mathematical vocabulary is used and the strength of using it properly. This is needed by engineering PhD's when reading papers, which will often use the common language of mathematics, and in particular when writing papers. Moreover, it is crucial, that engineers understand when a given mathematical toolbox is applicable and when it is not. As an example: In favourable cases, differential equations have unique solutions, but this is not always true, and trying to approximate a solution in such cases may lead to results which are simply wrong. The topics covered are: metric spaces, convergence, continuity, compactness, completeness. Vector Spaces and linearity. Korovkins theorem on polynomial approximations via Bernstein polynomials. The Banach Fixed Point Theorem. Existence and uniqueness results for ordinary differential equations. The approach in the course is to stress the necessity of precise mathematical formulation, and, in particular, to give examples where the intuitive answer is not correct.

Organizer: Professor Morten Nielsen, email: mnielsen@math.aau.dk

Lecturers: Professor Morten Nielsen

ECTS: 4

Time: 1, 4, 6, 13, 15, and 18 December 2017

Place:

Zip code: 9220

City: Aalborg

Number of seats: 30

Deadline: 10. November 2017 

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 5,000 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 three 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.

Welcome to Nonlinear Differential Equations and Dynamical Systems


Description: Models for physical systems and engineering designs are often formulated in the mathematical language of systems of differential equations. To analyse the behaviour of such a system, a basic knowledge in the theory of dynamical systems is highly recommended. While linear algebra methods (decomposition of matrices) suffice to understand and even to solve systems of linear differential equations, it is in general impossible to find formulas for the solutions of nonlinear differential equations. Instead, one uses geometry based methods to obtain qualitative information about the behaviour of the solutions. Some of the catch words are: Critical points, equilibria, periodicity, invariant sets and manifolds, stability theory (Lyapunov and Poincaré), perturbations and bifurcations, chaos and attractors.
The course will be based on lectures, exercises, and on computer experiments in computer algebra systems like MAPLE (or interactive web-based solvers). It is addressed to PhD-students interested in physical modelling and stability questions related to dynamical processes. It should be of interest to students within control theory, medical electronics, signal processing, mechanical and civil engineering, physics and mathematics.
Prerequisites: A basic knowledge of mathematics, as obtained through engineering studies at Aalborg University.

Organizer: Lisbeth Fajstrup, Associate Professor, email: fajstrup@math.aau.dk

Lecturers: Lisbeth Fajstrup, Associate Professor, Martin Raussen, Associate Professor and Professor Rafael Wisniewski

ECTS: 3

Time: November 6th, 8th, 10th, 14th and 16th

Place: 

Zip code: 

City: 

Number of seats: 40

Deadline: 16th of October


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 5,000 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 three 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.

Welcome to Mixed Models with Biomedical and Engineering Applications

Description: Mixed models provide a flexible framework for analyzing data with multiple sources of random variation and they are indispensable in many medical, biological, and engineering applications. When treatments are tested in medical applications, the responses for individuals receiving the same treatment often vary due to unobserved genetic factors and this variation must be taken into account when comparing ifferent treatments. Similarly, in agricultural field trials, random soil variation affects the yield within plots. In quality control applications, the variability of the output of a production process may, apart from random noise, e.g. depend on the batches of raw material used and the employee involved in the manufacturing process. The course will provide an introduction to statistical analysis with linear mixed models. Linear mixed models is a unified framework for classical random effects ANOVA models, random coefficient models and linear models for longitudinal data with associated user-friendly implementations in R and SPSS. Linear mixed models moreover provide generalizations of the classical models to complex data not covered by he standard statistical toolbox. The course will focus on modeling with mixed models, on how a statistical analysis can be carried out for a mixed model, and on interpretation of models and results. Hands-on experience with real data will be obtained through computer exercises. Prerequisites: A basic knowledge of statistics (linear regression) and probability theory (random variables, expectation variance and covariance) is expected.

Organizer and lecturer: Professor Rasmus Waagepetersen, e-mail: rw@math.aau.dk

ECTS: 1,5

Time: 3 and 10 October 2017

Place:

Zip code: 9220

City: Aalborg

Number of seats: 20

Deadline: 12 September 2017

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 5,000 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 three 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.

Welcome to: Advanced signal processing in joint time-frequency and time-scale domains


Description:
The course addresses advanced principles of analysis of information carried by various biological signals. Time or frequency domain analysis often fails to accurately capture the dynamics of non-stationary biological processes modulating the signals recorded by sensors. Basic principles of signal processing such as features extraction and filtering used in the time or frequency domains are extended in the joint time-frequency domain and in the joint time-scale domain. The course is intended to provide the understanding and practical use of the Wigner-Ville, Choi-Williams, Rihaczek, Cone-shaped and Adaptive-kernel quadratic time-frequency distributions, as well as of the wavelet transform with various types of wavelets. The course provides both lectures and hands-on workshops with emphasis on the practical aspects such as advantages and limitations of processing of signals recorded from the brain, muscles, and heart.

Prerequisites:
Basic knowledge in signal processing, mathematics and Matlab.

Learning objectives:
The course aims to provide the students with skills and knowledge in advanced signal processing as a valuable tool in designing of experiments and interpretation of data acquired.

Teaching methods:
Lectures and hands-on workshops distributed over 3 days with feedback from students after each session/day.

Criteria for assessment:
Evaluation of knowledge gained and associated to a specific task provided during the workshop will be performed during and oral assessment.

Key literature:
B. Boashash, Time-Frequency Signal Analysis and Processing, 2nd Edition, Academic Press, 2015

L. Debnath, Wavelet Transforms and Time Frequency Signal Processing, 2001


Organizer: Associate professor Romulus Lontis, lontis@hst.aau.dk


Lecturers: Associate professor Romulus Lontis, lontis@hst.aau.dk

ECTS: 1,5

Time: 29 March and 6 April 2017

Place: Fredriks Bajers Vej 7, room Frb 7E/3-209 

Zip code:
9220

City:
Aalborg Øst

Number of seats: 30

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 5,000 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 three 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.


Deadline: 16 March 2017