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Curriculum

The curriculum of the IPHS allows students to individually tailor a course program to fit their particular educational background and their specific research interests. The formal coursework is required for the completion of the dissertation and encompass a minimum of four hours per week and term over four terms.

The attended courses should be choosen by the students and should be documented on the IPHS attendance forms.

The courses which the candidates have to take comprise both mandatory and elective modules. The latter may involve a large number of subject areas.

Mandatory Modules

Lectures, seminars, exercises, lab courses and other activities in the following areas:

  1. Seminars on Project Development (e.g. 3x TAC-Meetings)
  2. Medical Statistics (see below for the Statistic Workshop lectured in English)
  3. Ethics, Theory of Sciences and Legislation in Research (see below)
  4. Working and Publishing in Science / Science Communication / Good Scientific Practice (see below)

 

Elective Modules

Lectures, seminars, exercises, lab courses and other activities in the following areas:

  1. Evidence-based Medicine / Evaluations related to Health Economics
  2. Healthcare System and Society
  3. Translational Research
  4. Health Services Research
  5. Human Biology
  6. Pathology, Pharmacology
  7. Biochemistry and Molecular Biology
  8. Chemistry
  9. Physics
  10. Empirical Social Research
  11. Medical & Social Diversity
  12. Mathematical & Statistical Modeling
  13. Images of Man in Research
  14. Psychology / Psychiatry

Attendance forms

Please list all attended course on your attendance sheets.

Please downlad the attendance forms

Attendance form guest speakers
(PDF)
Attendance seminars
(PDF)
Information curriculum
(PDF)
Letter Curriculum
(PDF)

Lectures, courses and seminars of the University of Cologne

An overview of all lectures, courses and seminars of the University of Cologne can be seen in KLIPS 2.0: Anmelden - KLIPS 2.0 - Universität zu Köln (uni-koeln.de) (Faculty -> Faculty of Medicine -> Division -> Courses)

Some of these lectures and seminars might be of interest (according to your project) for postgraduates of the Interdisciplinary Program Health Sciences at the University of Cologne.

Guest Speaker seminars

In additional to courses and seminars on a regular basis during the semester guest speaker seminars can be taken. For guest speaker seminars please visit: http://www.life-science-vortraege.uni-koeln.de/ or the annoucements of the University of Cologne or the University Hospital Cologne.

Good Scientific Practice

The next workshop on Good Scientific Practice lectured in English by Prof. Dr. Nicole Skoetz will take on the following dates (live, in-person):

1. Tuesday 25.06.24, 09:15-11:15 (2 hrs) in the Oratorium (MEK-Forum, Joseph-Stelzmann-Str. 20)

2. Thursday 27.06.24, 09:15-11:15 (2 hrs) in the Oratorium (MEK-Forum, Joseph-Stelzmann-Str. 20)

Course Language: English

Please note, both dates are mandatory to complete the module (you will receive a participation certificate). Please register here (deadline for registration 19.06.24).

Research Ethics and Theory of Science

The next workshop on "Research Ethics and Theory of Science" lectured by Dr. Christian Hick (Institute for the History and Ethics of Medicine) will take place in Q2 2024.

Statistics Workshops

The next workshop on Statistics with the Software "R" lectured in English by Prof. Dr. A. Tresch will take place in the Winter term 2024/2025 (dates tbd. Registration call will be announced in due time).

Below you will find further details of the last statistics workshop. Please note the "Prior Knowledge" part.

Learning Competencies

This workshop teaches the basics of data analysis using the programming language R on RStudio Server Pro. You will learn to apply statistics to high-dimensional, biological data. You will acquire a repertoire of computer-based methods for supervised and unsupervised learning tasks and estimation problems as they occur in life science data. You will become aware of the peculiarities of high-dimensional statistics and large data sets (e.g. curse of dimensionality and multiple testing) and will learn to critically assess third-party analyses.

Contents

Data description, Hypothesis testing, Clustering, Dimensionality reduction, Data visualization, Regression and linear models, Classification, Cross Validation and Bootstrapping, Feature selection, Reproducibility.

Prior Knowledge

A solid understanding of the basic statistics taught in foundation courses is required. Experience with the R programming language in particular is not necessary, but rudimentary knowledge of programming is. This workshop focuses on the application of statistical methods and not programming. Skills in other scripting languages, like Python for example, can be easily transferred to R.

The workshop makes use of an RStudio Server Pro instance. VPN access to the UKLAN and a current web browser is required.

For further lectures and courses offered by the Institute for Medical Statistics and Bioinformatics please click here.

Working and Publishing in Science / Science Communication

The University of Cologne offers a range of opportunities: