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Faculty of Medicine

Doctoral Program Clinical Science

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.

Program

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.

Conditions

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.

Doktoratsordnung vom 9. Februar 2022 (PDF, 64 KB) 
 

Guidelines

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

Application

Conditions

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*

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

Application Deadline

May 1, 2024

Fees

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.

Application Process

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.

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.

Admission

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.

Program Management

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, M.A., 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
  • Prof. Barbara E. Stähli, MD website
  • Prof. Susanne Wegener, MD website

Additional members of the doctoral program committee are:

  • Lea Schwab, MLaw, M.A., Program Coordinator (contact)
  • Anna Joachimbauer, MD, PhD Student Representative
  • Parisa Rahimzadeh, MD, 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.

Member's Meeting

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.

Curricular Content

Compulsory Modules

Introduction to Epidemiology (Milo Puhan, Viktor von Wyl et al.)

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 2024

 

Advanced Medical Research Methods (Milo Puhan, Henock Yebyo, 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.

Course Description:

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.

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.

Next conduct in Fall Semester 2024

 

Clinical Biostatistics (Leonhard Held, Stefanie von Felten)

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.

Next conduct in Fall Semester 2024

 

Case Studies in Clinical Biostatistics (Ulrike Held, Manja Deforth) (1 ECTS Credit)

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).

Conduct: Thursdays, February 22 – April 4, 2024, 10:15 – 11:45 a.m., small seminar room (i.e. rooms 290 and 288), Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich

 

PhD Seminar (Bea Latal, Alisa Berger, Markus Grütter)

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.

Career Development, Tuesday, April 23, 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

Bibliometrics and Social Media for Researchers, Tuesday, May 14, 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

Scientific Integrity, Tuesday, May 28, 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

 

Optional Courses

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 2024

 

Basic Introduction to Programming in R Focusing on Medical Research (Ulrike Held, Monika Hebeisen)

The course covers basics of programming and data formats in R, and the essential steps of a data analysis including data manipulation, descriptive statistics, statistical tests and graphical representations. The course is taylored to medical research and limited to 20 participants.

Next conduct in Fall Semester 2024

 

Get R_eady: Introduction to Data Analysis for Empirical Research (Ulrike Held, Monika Karin Hebeisen, Stefania Iaquinto)

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: Thursdays, April 11 – April 25, 2024, 2:00 – 5:00 p.m., KO2-D-54, Karl-Schmid-Strasse 4, 8006 Zurich

 

Implementation Science in Health Care (Lauren Clack, Rahel Naef et al.)

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, February 28 May 8, 2024, 09:00 11:45 a.m., Institute for Implementation Science in Health Care, UNK-E-2, Universitätsstrasse 84, 8006 Zurich

 

Applied Implementation Science in Health Care (Lauren Clack, Rahel Naef)

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):

  • Human-centered design (co-design) and implementation science
  • Tailoring implementation strategies
  • Evaluating context
  • Research logic models
  • Theories, Models, and Frameworks
  • De-implementation
  • Quantitative & qualitative measures
  • Health economic evaluation and implementation science
Next conduct in Fall Semester 2024

 

Statistische Modelle mit R (Christina Ramsenthaler)

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:

  • lineare Modelle und deren Spezialfälle (LM: t-Test, ANOVA, Regression);
  • Regressionsmodelle für ausgewählte Datentypen wie Zähldaten und zweiwertige Daten (GLM: Poisson, logistische Regression);
  • multivariate Verfahren (Hauptkomponenten- und Faktoranalyse);
  • Einführung in Überlebensanalysen (survival analysis);
  • hierarchische Modelle (LMM: lineare gemischte Modelle); 
  • ausgewählte Methoden der Metaanalyse;
  • Arbeit mit dem Grafikpackage ggplot2, Arbeit mit den Packages im Tidyverse und Einführung in RMarkdown zur Berichterstellung.

Conduct: Tuesdays, February 20 March 12, 2024, 10:00 a.m. – 05:00 p.m.,
on February 20, 2024, room 286, Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich
on February 27 and March 12, 2024, by Zoom
on March 5, 2024, room
274, Careum 2, 2nd floor, Gloriastrasse 18, 8006 Zurich

 

Überfachliche Kompetenzen

Zu den Kursen des Graduate Campus für Doktorierende im Frühjahrssemester 2024 gelangen Sie hier.

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Contact

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

Weiterführende Informationen

Application

Application to the doctoral program
track 1: click here
Application to the doctoral program
track 2: click here
Next deadline:
Wednesday, May 1, 2024, 11:59 p.m.

Track 1 Application

Candidates seeking PhD positions may apply for a PhD position within the PhD program Clinical Science and use the following link to apply. The job announcement will be posted here in due course.

Track 2 Application

Candidates who have a PhD position use the following link to apply.

Employment Rules

Employment should be in line with the rules of the Swiss National Science Foundation (SNF).

lifesciencezurich

Life Science Zurich Graduate School

More about Life Science Zurich Graduate School

Promotion Regulation

The promotion regulation for the title Doctor scientarium medicarum (Dr. sc. med.) of the University of Zurich can be found under the following link (available in German only).

Regulations for the General Outline of Rights and Responsibilities

The Regulations for the General Outline of Rights and Responsibilities of the Faculties for Teaching and Research Assistants and Doctoral Candidates can be found under the following link. 
Regulations for the General Outline of Rights and Responsibilities

Curriculum

Information on the modules can be found in the course catalogue under the following link.

Recommended MOOCs

The doctoral program committee recommends the following high-quality massive open online courses (MOOCs) on the topic of systematic review and meta-analysis:

Summary of Teaching Activities

This form is to be completed and signed by the PhD student at each annual PhD committee meeting, endorsed by the responsible professor.

Guidelines Multiple Affiliations

The guidelines should be followed when specifying the affiliation in all publication. This assures recognition of the scientific achievements.

Information

Information on the promotion within this program:

Fact sheet Completing a Thesis in the Doctoral Program Clinical Science DO 2022

Example of the cover sheet of your thesis:

Title page

Please follow the instructions concerning the print of your thesis. Spiral binding is not permitted.

Conflicts?

The following contact persons and counseling centers are available to you in the event of a conflict:

Program Specific Consulting
Lea Schwab, MLaw, M.A.
Conflict Management for PhD Candidates
Psychological Counseling Services
Advice on Problems Related to Employment, Job Specifications and the Position as a Member of the UZH Mid-Level Staff
Association of Junior Researchers of the University of Zurich (VAUZ)
Advice also for External PhD Candidates in Case of Difficulties at the Workplace
Employee Assistance Office (MBS)
Contact Point for Suspected Scientific Misconduct Among UZH Researchers
Ombudsperson and Deputies Research Integrity

We congratulate

our PhD student: 
Antonio Giulio Gennari, MD, for the Anna-Müller-Grocholski-Prize 2023 of the Swiss Society of Neuropaediatrics for his work: "Lesion volume and spike frequency impact perfusion in focal cortical dysplasia: a pediatric arterial spin labeling study" (1st prize in the scientific work category).

Florian Alexander Wenzl, MD, for the FAN Award 2023 in the field of medicine and natural sciences for his research on the topic: "Sex-specific evaluation and redevelopment of the GRACE score in non-ST-segment elevation acute coronary syndromes in populations from the UK and Switzerland: a multinational analysis with external cohort validation."

our graduates:
Melanie Ehrler, PhD, for the FAN Award 2024 in the field of medicine and natural sciences for her research project: "Die Verbindung zwischen Herz und Hirn – ein interdisziplinärer Ansatz zur Verbesserung der Entwicklung von Kindern mit angeborenem Herzfehler." 

Kevin Sven Akeret, MD, PhD, for the Annual Prize 2023 of the Faculty of Medicine for his dissertation: "Cerebrospinal fluid hemoglobin in the pathophysiology, diagnosis and therapy of aneurysmal subarachnoid hemorrhage related secondary brain injury".

Florentia Dimitriou, MD, PhD, PD, for the Research Fellowship 2023 of the Siegenthaler Foundation for her research focus: "Delineating the role of the microbiome and immunotherapy response across melanoma subtypes", the Skin Cancer Award 2022 from the Association for Skin Cancer Research at the University Hospital Zurichfor her research project: "Serum and tissue biomarkers associated with immune-related adverse events (irAEs) in patient treated with anti-PD1-based immune checkpoint inhibitors" and to the Georg Friedrich Götz-Prize 2022 of the UZH Foundation for her research topic: "Immunotherapy in advanced mucosal melanoma".

Egle Ramelyte, MD, PhD, for thePfizer Research Prize 2022 for her research topic: "Effects of oncolytic viruses on cell function in skin lymphoma" and for the Skin Cancer Award 2020 from the Association for Skin Cancer Research at the University Hospital Zurichfor her research project: "Ocolytic virotherapy mediated anti-tumor response through a single-cell’s perspective".