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The methods seminar is not only an important part of the curriculum but also very important for interdisciplinary exchange between students of the different labs. It is the only course all students independent of the lab have to take. This is the place where students meet each other and get to know each other. It is not a classical lecture but generally a group of students is responsible for organising one session with support of a faculty. Therefore students of different labs have to collaborate and organize a lecture. Contentwise, we are looking at very broad topics such as visualisation, regression, personalized medicine, reproducibility & ethics, spatial epidemiology and biomedical & research ethics.
In order to be awarded the ECTS you have to book the methods seminar (STA880DP) via the UZH module booking system (OLAT is not a booking system, it is an e-learning system into which the students who booked the module are imported).
We expect that you only book the module if you actively participate in the preparation of a group session and we rely on your responsibility and on peer pressure to prevent abuse of this simple system of awarding ECTS. If you are late in booking or if you need to book a spring/fall semester version for the second time, contact the Program Coordinator. Even if you don't book the module you are invited to come to the sessions and/or to actively participate in their preparation: you will learn nothing non-useful for your future career!
Time: Wednesdays, 15.00 – 17.00 Venue: HIT-E-03 (Hirschengraben 82). Lead: Roger Kouyos
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Dates |
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September 18 |
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September 25 |
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October 2 |
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October 23 |
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November 6 |
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November 13 |
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November 20 (moving date / potentially faculty talk) |
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Topics |
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Introduction to Mathematical Modelling |
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Key concepts and tools in mathematical models |
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Adding layers of complexity: population structure and demographics |
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Adding layers of complexity: stochasticity, periodicity, and seasonality |
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Multistrain models, pathogen evolution, and phylodynamics |
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Mathematical models beyond infectious disease dynamics |
| Year | Topic | Lead |
|---|---|---|
| Spring 24 |
Creating, Maintaining, and Operating a Free Research Software Environment |
Torsten Hothorn |
| Fall 23 | Bayes for everyone | Malgorzata Roos |
| Spring 23 | Causal inference methods in Epidemiology | Miquel Serra Burriel |
| Fall 22 | Qualitative research methods in Epidemiology / mixed-methods | Felix Gille |
| Spring 22 | Personalised medicine | Milo Puhan |
| Fall 21 | Causal Interpretations from randomised trials: The devil is in the detail | Torsten Hothorn |
| Spring 21 | Visualization | Milo Puhan |
| Fall 20 |
Misconceptions and misspecifications in the interpretation of evidence |
Torsten Hothorn |
| Spring 20 | Introduction to machine learning | Mark Robinson |
| Fall 19 | Reproducibility | Eva Furrer |
| Spring 19 |
Biomedical and research ethics |
Milo Puhan |
| Fall 18 | Spatial epidemiology | Oliver Grübner |
| Spring 18 | Regression | Torsten Hothorn |
| Fall 17 | Visualization | Milo Puhan |
| Spring 17 | Reproducibility and ethics | Torsten Hothorn |
| Fall 16 | Misconceptions and missspecifications in the interpretation of evidence | Leonard Held |
| Spring 16 | Personalized medicine | Milo Puhan |
| Fall 15 | Visualization | Milo Puhan |
| Spring 15 | Reproducibility and ethics | Torsten Hothorn, Milo Puhan |
| Fall 14 | Introduction to Epidemiology | Milo Puhan |
