Graduate School of health and Medical Sciences

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Advanced topics in causal inference
Provider: Faculty of Health and Medical Sciences

Activity no.: 3356-26-00-00	There are 17 available seats
	Enrollment deadline: 21/09/2026

Date and time	20.10.2026, at: 09:00 - 29.10.2026, at: 16:00
Regular seats	20
Course fee	6,960.00 kr.
Lecturers	Erin Gabriel
ECTS credits	2.80

Contact person	Susanne Kragskov Laupstad E-mail address: skl@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration SUND E-mail address: phdkursus@sund.ku.dk

Enrolment guidelines This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Aim This four-day intensive course aimed at Ph.D. students in Math, Computer Science, Biostatistics, Epidemiology, Health Data Science, or Statistics who already work in causal inference and in particular statistical methods for causal inference and want information about an advanced topic. When participating in this course, you will get a working knowledge of the conceptual roots of a set of special and advanced topics in causal inference, as well as hands on experience using the most common methods used for that topic. Learning objectives A student who has met the objectives of the course will: 1. Be aware of and be able to discuss and use concepts from the special topics that will rotate each time the course is given. Content this course occasion: Day 1: Causal inference in time-to-event settings and TBD Day 2: Semi-parametric theory and TBD Day 3: Partial identification and further causal inference methods for time-to-event outcomes Day 4: A critical look at mediation separable effects and TBD Statistical software We will be working with the open source statistical software R using the interface RStudio. To participate in the course you must bring your own laptop with R and RStudio installed. Prerequisites Familiarity with R programming is necessary for taking part in the exercise classes and for completing the exercise problems. Introduction to causal inference or other similar course, some mathematical theory of causal inference and statistics, some basic understanding of calculus. This course will be very hard mathematically for people with no statistical background, but it may also not be extremely rigorous mathematically. Participants Ph.D.-students. In case of vacant seats also other medical researchers. Max. 20 participants. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Biostatistics and Bioinformatics Public Health and Epidemiology Language English Form Lectures and interactive learning for all 6 hours Course director Erin Gabriel, Professor Section of Biostatistics KU Teachers Mats Stendrud, Associate professor Institute of Mathematics EPFL Ruth Keogh, Professor London School of Hygiene and Tropical Medicine Vanessa Didelez, Professor BIPS Additional teachers TBD Torben Martinussen, Professor KU Pawel Morzywolek, Assistant Professor KU Erin Gabriel, Professor KU Dates Tuesdays and Thursdays: 20, 22, 27, 29 October 2026, all days 9-16 Course location CSS Registration: Please register before September 21 September 2026 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment.

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