Table of contents
Doctoral Program Clinical Science
The doctoral program Clinical Science, which focuses on research with healthy or sick people in a clinical setting, has been established to open a university postgraduate qualification opportunity in the field of clinical research. The university hospitals will keep on promoting clinical research, making this program a true trendsetter.
The Clinical Science program allows candidates to carry out an in-depth clinical research in the field of medicine. It is open to highly motivated candidates who have proven to be academically outstanding and show a strong interest in clinical research.
This program is coordinated by the Dean’s Office of the Faculty of Medicine.
The doctoral program consists of original research as well as of curricular content, with mandatory and optional modules of at least 16 ECTS points, for which a minimum of three years in full-time employment is scheduled. However, in justified cases exceptions to this may be authorized by the doctoral program commission.
In order to apply for this doctoral program, candidates must have a university degree of master in either medicine, biomedicine, biology or psychology. Further academic qualifications which are compulsory for eligibility as well are listed in the following document “Doktoratsordnung”. All candidates must have good skills in English.
The guidelines govern the doctoral program Clinical Science, which is offered at the faculty of Medicine of the University of Zurich. They formalize the promotion regulation for the title Dr. sc. med. (equivalent to a PhD) from the Faculty of Medicine of the University of Zurich
In order to apply for this doctoral program, candidates must at least hold a university master's degree in either medicine, biomedicine, biology or psychology. Further academic qualifications that are compulsory for eligibility as well are listed in the document "Doktoratsordnung". All candidates must have good skills in English and German.
Double matriculation in the general doctorate of the Faculty of Medicine (Dr. med.) and in the PhD program Clinical Science is not planned. If, at the time of your application for the PhD program, you are about to graduate as Dr. med., please indicate this in your application. Otherwise, the simultaneous completion of the general doctorate and the PhD program is not intended.
*Applies to future PhD students
July 1, 2022
The registration fees are set by the Student Administration Office of the University of Zurich and also apply to doctoral students. Doctoral students must be enrolled throughout the entire period of study.
Applications must be submitted by using the Online application portal of the Life Science Zurich Graduate School exclusively. Applications sent by e-mail or mail will not be accepted.
There are two ways to apply for the Clinical Science doctoral program:
Track 1: Applicants without a PhD position have to apply via track 1. Within the doctoral program, PhD positions will be advertised competitively in each application round. Open positions will be published on www.jobs.uzh.ch in spring/autumn. All applications received via track 1 will be checked for their suitability for the open positions. In an interview, the admissions commission examines the admission to the doctoral program. The person who has an open PhD position also takes part in the interview.
Track 2: Applicants who already have a supervisor for their PhD-project have to apply via track 2. In an interview, the admissions commission evaluates the qualification and motivation of the candidate. Please do not start your PhD-position before the interview.
For the applications track 2 the deadlines July 1 and December 1 apply.
To receive the link for the online application tool, please contact: firstname.lastname@example.org.
License to Practice Medicine
For some PhD positions, the licence to practice Medicine from the Swiss Bundesamt für Gesundheit (BAG) is mandatory for candidates with a master’s degree in Medicine that was not issued in Switzerland.
Applications will be reviewed by the admissions committee after the deadline. Please refer to your personal Glowbase account to find out about your current status. Interviews will be held in English and German.
The general responsibility for the doctoral program Clinical Science lays within the program committee which is set up by the Faculty of Medicine.
The doctoral program is managed by:
- Prof. Beatrix Latal, MD, Director
- Lea Schwab, MLaw, Program Coordinator
The current senior members of the doctoral program committee are:
- Prof. Beatrix Latal, MD, Director website
- Prof. Milo Puhan, MD, PhD, Deputy Director website
- Prof. Maries van den Broek, PhD, Vice Dean of Research website
- Prof. Dr. phil. Gerhard Rogler, MD website
Additional members of the doctoral program committee are:
- Lea Schwab, MLaw, Program Coordinator (contact)
- Nina Derron, MSc ETH in Health Sciences and Technology (HST), PhD Student Representative
- Felix P. Schmidt, MSc in Pharmacy, PhD Student Representative
This committee decides on the development of the curriculum, coordinates the curricular requirements, is involved in the selection and admission of candidates and supports the cooperation with the Faculty of Medicine.
The Member's Meeting consists of faculty members taking part in the program. In addition, supervisors who are not faculty members but supervisors of students (mostly with private research programs) may be elected members. Tasks of the General Assembly include the strategic direction and organization of the doctoral program, the selection of the Directress or the Director as well as their deputies, and active participation in the doctoral program.
Introduction to Epidemiology (Milo Puhan)
The overall goal of this 4-week block course Introduction to Epidemiology is to introduce students to the major questions of clinical and epidemiologic research and to methods to address these questions. The course follows an overall framework (Figure) that describes the course of scientific discovery from the detection and burden of disease and its causes, to diagnosis and prognosis of disease up to the development and evaluation of preventive and treatment interventions and their consequences for population health. We will discuss study designs in the context of existing knowledge and the type of evidence needed to advance knowledge for specific questions. Thereby, students learn to combine subject knowledge and methods expertise to design, conduct and interpret substantive medical research. The course will provide a basis for further studies and research in the fields of Medicine and Public Health (on Master or PhD level), both of which are very dynamic and diverse fields.
Next conduct in Fall Semester 2022
Advanced Medical Research Methods (Milo Puhan, Henock Yebyo and Miquel Serra-Burriel)
Modulleitung: Prof. Milo Puhan, MD, PhD
Link: Epidemiology, Biostatistics and Prevention Institute
This course has been designed for Clinical Science PhD students to learn and experience the scientific and practical aspects of applied clinical research methods.
Advanced Medical Research Methods
The aim of this course is to introduce students to advanced research methods and apply previous knowledge in epidemiology and biostatistics into real-life research. To achieve this, the lectures will cover novel study designs (special designs of RCTs and observational studies like factorial RCTs and nested case-control studies), advanced statistical methods (propensity scores, missing data). We will introduce special topics in epidemiology related to modifiable risk factors (nutrition and physical activity) which can be applied to a variety of outcomes, as well as current topics in research (molecular epidemiology, big data and translational research). The ‘lab’ sessions will provide practical techniques, (using R) that will further expand the set of tools that the future PhDs will be able to apply in their research. Furthermore, the practical experience will be complemented by the group exercise of writing protocol for a fictional RCT (designed and developed during the semester) under a guidance of an epidemiologist/researcher at the ZAM.
Three groups of 3 to 4 students, preferentially with diverse interests and backgrounds, will design a feasible RCT to address a real public health problem. One lecturer will be assigned per group. Further administrative information will be provided at the beginning of the first lecture.
Next conduct in Fall Semester 2022
Clinical Biostatistics (Leonhard Held)
The aim of the course "Clinical Biostatistics" is to give students an introduction to statistical methods in clinical research.
The following topics will be addressed: randomized controlled trials, bias, hypothesis tests and sample size calculation, randomization and blinding, confidence intervals and p-values, analysis of continuous and binary outcomes, multiplicity, subgroup analysis, protocol and protocol deviations, some special designs (crossover, equivalence, and clusters), analysis of diagnostic studies, analysis of agreement.
Next conduct in Fall Semester 2022
Case Studies in Clinical Biostatistics (Ulrike Held)
The aim of the course is to give students practice in different stages of dealing with a clinical research project: study design, primary outcome definition and sample size calculation, plausibility checks, data analysis and modelling, computation, interpretation, and communication of results. In five research projects, students will face real-world problems typically associated with study design, data analysis and reporting.
Project 1: Descriptive statistics and graphical display of data with different levels of measurement, including continuous, ordinal, and dichotomous variables.
Project 2: Comparison of the means of two populations, hypothesis testing with parametric and non-parametric tests, confidence intervals.
Project 3: Research protocol for a clinical study, primary outcome, secondary outcomes, sample size determination.
Project 4: Multiple regression analysis, including missing data, plausibility checks, for continuous outcomes.
Project 5: Categorical data and multiple logistic regression.
The statistical software R will be used. Students are encouraged to work in groups. At the end of each project, students will be asked to hand in individual reports and present their results in a 15 min talk. The talks and reports will be assessed. In order to enroll in this course it is mandatory to have passed CS16_003 Clinical Biostatistics (Vorlesung und Übung).
Conduct: Thursdays, 10:15 – 11:45 a.m., room 290, Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
Winning the Publication Game (Jürgen Barth)
Jürgen Barth teaches in this module the relevant steps to publish a manuscript. Participants will have the chance to exercise the process. This process includes the preparation work, writing the paper and submitting it. There are 10 major topic involved in the successful publication of a paper. Publication starts with the identification of the target group. Further, the main message has to be shaped. The lecturer gives advice on the covering letter for the editor. He instructs how to handle the comments of the reviewers.
Prerequisite for the participants is to have specific plans for a manuscript, that will be submitted within 6 months. In the course, the relevant steps for the submission of the manuscript are conferred. The lecturer will deal with all individual manuscripts.
All PhD-Students in their 2nd or 3rd year are welcome to register. By actively participating and doing the exercises, the participants will be able to develop the skills to win the publication game.
Next conduct in Fall Semester 2022
PhD Seminar (Martina Gosteli, Markus Grütter, Beatrix Latal)
The objective of this course is to have a more detailed look into diverse research topics, methods and problems. Sessions are either based on a talk by an experienced researcher followed by a student lead discussion or on a general research topic which is being prepared by a group of PhD students for discussion with peers. Examples for discussed topics include personalized medicine, biomarkers, evidence based medicine, graphs in publications a.o. This PhD Seminar will take place every four weeks during the semester.
Bibliomatrics and Social Media for Researchers, date, time and place will follow shortly
Scientific Integrity, date, time and place will follow shortly
Career Development, date, time and place will follow shortly
Implementation Science in Health Care (Lauren Clack, Rahel Naef) NEW
Implementation science is the scientific study of methods to promote the systematic integration of research findings and evidence-based practices into care delivery and the de-integration of low value care. Implementation science is a newer field of study that addresses the know-do gap in health care and builds on the insight that proving effectiveness of an innovation (practice, model of care, intervention, treatment modality etc.) does not automatically translate into effective adoption in clinical practice.
Implementation science therefore aims to:
- increase and accelerate the adoption of research findings and evidence-based practices;
- scale-up effective interventions to different contexts;
- develop knowledge on implementation strategies that are tailored to contextual barriers and enablers to adoption and research use;
- increase the involvement of clinicians, patients, families, and the public in research;
- achieve knowledge circulation i.e., to enable the transfer of knowledge from practice to research.
In this course, students will gain an understanding of the role of implementation science in clinical health research, familiarize themselves with implementation science methods, and develop skills by applying implementation science methods in their field of research.
Conduct: Wednesdays, March 2 – May 11, 2022, 09:00 a.m. – 12:00 p.m., room UNK-E-2, Universitätsstrasse 84, 8006 Zurich
April 27, 2022 is reserved for project group work.
Statistische Modelle mit R (André Meichtry)
Statistische Modelle sind vereinfachte Darstellungen von Prozessen, die reelle Daten generieren. In wiederholtem Zusammenspiel von Simulation und Analyse mit der Open-Source Statistik-Software R wird in die wichtigsten Modelle der Gesundheitswissenschaften eingeführt:
- lineare Modelle und deren Spezialfälle (LM: t-Test, ANOVA, Regression);
- Regressionsmodelle für ausgewählte Datentypen wie Zähldaten und zweiwertige Daten (GLM: Poisson, logistische Regression);
- multivariaten Verfahren (Hauptkomponenten- und Faktoranalyse);
- Einführung in Überlebensanalysen;
- hierarchische Modelle (LMM: lineare gemischte Modelle);
- ausgewählte Methoden der Metaanalyse.
Conduct: Fridays, February 25 – March 18, 2022, 10:00 a.m. – 05:00 p.m.,
on March 4 and 18, 2022, by zoom
on Feburary 25 and March 11, 2022, room 271, Careum 2, Gloriastrasse 18, 8006 Zurich
University of Zurich
Dean's Office /
Office of the Board of Directors of
the Academic Medicine Zurich (UMZH)
Lea Schwab, MLaw
Telefon: +41 44 634 48 39