This master’s curriculum provides a thorough grounding in clinical research methods, combining theoretical foundations with practical skills needed to design, run and report clinical studies. You will learn how to develop clear research questions and select appropriate study populations, and gain hands-on experience with trial processes such as randomisation, blinding, electronic data capture, interim monitoring and scientific reporting (including manuscript writing). Core statistical topics are covered in depth, from data classification and common statistical tests to sample size calculation, survival analysis, handling missing data and meta-analysis. The first module also reviews the spectrum of study designs and clinical trial phases (phase 0–IV), and it includes the content of the PPCR programme (recognition of this programme may be possible).
The second module builds applied skills for analysing and communicating clinical data. It focuses on applied biostatistics, principles of data visualisation, and sources of clinical data, capped by a practical R/RStudio workshop so you can apply methods to real datasets and produce publication-ready figures and analyses.
The third module explores current and emerging topics shaping clinical research practice. You will practise scientific presentation and modern media communication, and study health economic outcome research. The syllabus also addresses large-scale and novel data approaches — big data and artificial intelligence (AI), real-world data (RWD) and real-world evidence (RWE) — and the methods used in health technology assessment (HTA).
Core modules and topics (concise)
Module One — Basics of Clinical Research (theory)
Module Two — Advanced Clinical Research (applications)
Module Three — Innovations in Clinical Research
This Master's programme expects applicants to come with a solid academic and professional background in clinical research. You must hold a qualifying university degree equivalent to 240 ECTS, demonstrate current engagement in clinical research, and have at least one year of professional work experience. In addition, enrolment in—or successful completion of—the PPCR course offered by the Harvard T.H. Chan School of Public Health is required.
When preparing your application, make sure your undergraduate/previous degree is recognised in your country of origin and that you can supply official transcripts and degree certificates. For the PPCR requirement you can submit either a registration confirmation or a completion certificate. Employment status and work experience are usually documented with an employer letter, contract, or an up-to-date CV showing dates and duties.
Graduates will be prepared for operational and analytical roles in clinical research such as clinical trial manager/coordinator, biostatistician or data manager, real-world evidence analyst, HTA or health economics specialist, regulatory affairs associate, medical writer, or positions within CROs and pharmaceutical companies. The programme's emphasis on study design, statistical methods, data capture/monitoring, R-based data analysis, manuscript writing and trial management equips students for roles that require designing and running clinical studies and interpreting complex clinical data.
Because admission requires current employment in clinical research and professional experience, the MSc is particularly suited to professionals seeking career advancement or transition into leadership/technical specialist positions. The mix of practical workshops and modules on modern methods (AI, RWD/RWE, HTA) also supports opportunities in health technology firms, research institutions, hospitals, regulatory agencies and consultancy roles; graduates may also pursue subject-specific research or PhD paths afterward, although no combined MSc–PhD programme is offered.
Technical University of Munich — München
Technical University of Munich — München
Hochschule Fresenius - University of Applied Sciences — Berlin
Ulm University — Ulm