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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 12 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
November 1, 2024
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 (for the links for Track 1 and Track 2 see at the bottom of the website in the teasers Application, Track 1 Application, Track 2 Application). 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 May 1 and November 1 apply.
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:
The current senior members of the doctoral program committee are:
Additional members of the doctoral program committee are:
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.
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.
Conduct:
Mondays, October 21 – November 18, 2024, 9:00 a.m. – 5:00 p.m., Rämistrasse 71, 8006 Zurich, KOL-G-210
Tuesdays, October 22 – November 19, 2024, 8:00 a.m. – 5:00 p.m., Karl Schmid-Strasse 4 resp. Rämistrasse 71, 8006 Zurich, KO2-F-151, KOL-G-210
Wednesdays, October 23 – November 20, 2024, 8:00 a.m. – 12:00 p.m., Rämistrasse 71, 8006 Zurich, KOL-G-210
Exceptions:
Monday, October 28, 2024, 9:00 a.m. – 5:00 p.m., Rämistrasse 71, 8006 Zurich, KOL-H-309
Tuesday, October 29, 2024, 8:00 a.m. – 5:00 p.m., Karl Schmid-Strasse 4 resp. Rämistrasse 71, 8006 Zurich, KO2-F-151, KOL-H-309
Wednesday, October 30, 2024, 8:00 a.m. – 12:00 p.m., Rämistrasse 71, 8006 Zurich, KOL-G-216
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.
Course Description:
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.
Group Project:
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.
Prerequisites:
Intro to Epidemiology or RCT course (BME361) & Basic course in Biostatistic (ie Clinical Biostatistics or similar) & experiences in R.
Conduct: Tuesdays, September 17 – December 17, 2024, 1:00 – 4:00 p.m., large seminar room (i.e. rooms 290, 288 and 286), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
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.
Please note that PhD students are asked to use the time between 12 and 15 h to prepare work for the lab.
Conduct: Thursdays, September 19 – December 19, 2024, 10:00 a.m. – 12:00 p.m. (lecture) and 3:00 – 4:00 p.m. (lab), Irchel Campus, Winterthurerstrasse 190, 8057 Zurich, Y03-G-91 (lecture) and online (lab)
The aim of the course is to give students practice in different stages of clinical research projects: study design, primary outcome definition and sample size calculation, plausibility checks, data analysis and modelling, computation, interpretation, and communication of results, as well as dissemination according to EQUATOR guidelines. In 3 research projects, students will face real-world problems typically associated with study design, data analysis and reporting. A focus of the course will be on good research practice, application of statistics knowledge and reproducibility. We will use the statistical programming language R in combination with R Markdown for reproducibility and dynamic reporting.
Project 1: Comparison of the means of two populations, hypothesis testing with parametric and non-parametric tests, confidence intervals. Baseline adjustment with ANCOVA model.
Project 2: Research protocol for a clinical study, primary outcome, secondary outcomes, sample size determination.
Project 3: Estimation of the treatment effect in a randomized experiment with a time-to-event outcome, Kaplan-Meier curves, Cox proportional hazards model.
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 without exception to have passed CS16_003 Clinical Biostatistics (Vorlesung und Übung).
Next conduct in Spring Semester 2025
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.
Biomarker, Tuesday, September 17, 2024, 4:15 – 5:45 p.m., large seminar room (i.e. rooms 290, 288 and 286), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
How to Perform a Search for a Systematic Literature Review, Tuesday, October 22, 2024, 4:15 – 5:45 p.m., large seminar room (i.e. rooms 290, 288 and 286), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
Graphs for Display of Data and Publications, Tuesday, November 26, 2024, 4:15 – 5:45 p.m., large seminar room (i.e. rooms 290, 288 and 286), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
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.
Conduct: Friday, November 29, 2024, 9:00 a.m. – 5:30 p.m., large seminar room (i.e. rooms 290, 288 and 286), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
Friday, December 13, 2024, 9:00 a.m. – 5:30 p.m., by Zoom
The course offers an introduction to data analysis in the transdisciplinary field of empirical research in the programming language R. The R system of statistical computing is openly available from https://www.r-project.org and provides a simple and flexible software environment for statistical analyses and graphics. Tailored to the application of empirical research the course covers basics of functions and data formats in R, as well as the essential steps of a data analysis including data manipulation, descriptive statistics, statistical tests and graphical representations. Reflections on research methodology and transdisciplinarity will take place and critical thinking will be enhanced.
Conduct: Fridays, October 18 – November 1, 2024, 2:00 – 5:00 p.m., Rämistrasse 71, 8006 Zurich, KOL-E-18
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:
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.
Next conduct in Spring Semester 2025
This module will help students to gain a deeper and applied knowledge of Implementation Science. Students will have the opportunity to tailor course content to their current projects and interests by selecting from a pre-defined list of implementation topics to be covered during the semester. Working in small groups, students will prepare their chosen topics and present them to the class. Every session will furthermore provide the opportunity to transfer learnings from the presented topic (s) to one’s own project. Topics to choose from (finalization in the first session):
Der Kurs widmet sich den wichtigsten statistischen Auswertungsmethoden für unterschiedlichste Arten von Studien (Experimentalstudien, Beobachtungsstudien (Kohorten-, Fallkontrollstudien, deskriptive Quer- und Längsschnittstudien), Sekundäranalysen (z. B. Metaanalysen)). Es werden die wichtigsten Auswertungstechniken quantitativer Daten und die wichtigsten statistischen Modelle der Gesundheitswissenschaften mit der Open-Source Software R besprechen:
Next conduct in Spring Semester 2025
Zu den Kursen des Graduate Campus für Doktorierende im Herbstsemester 2024 gelangen Sie hier.
University of Zurich
Dean's Office /
Office of the Board of Directors of
the Academic Medicine Zurich (UMZH)
Pestalozzistrasse 3
CH-8032 Zurich
Lea Schwab, MLaw, M.A.
Telefon: +41 44 634 48 39
E-Mail: clinical-science@dekmed.uzh.ch
