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Programme overview (based on your choices)

Erasmus Summer Programme (ESP)

For more information about the Erasmus Summer Programme (ESP), please go to:

www.erasmussummerprogramme.nl

Master

Master of Science in Health Sciences | 1 Year | FULL-TIME | 70 ECTS

For whom?

This MSc programme focuses on training students who are already educated in research methodology, but wish to take a step further in developing a successful career in health science research. This programme is also interesting if you want to enhance your chances of pursuing a PhD.

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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Public Health
  • Pharmaco Epidemiology
  • Medical Psychology
  • Biostatistics

Research Master in Clinical Research | 2 Years | FULL-TIME | 120 ECTS

For whom?

There is a great need for clinicians who can combine patient care and research. This Research Master programme is a unique opportunity for medical students to become clinical investigators and pursue an academic career simultaneously.

This programme for ambitious students with a Bachelor degree in Medicine or Biomedical Sciences. If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

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Research Master in Health Sciences | 2 Years | FULL-TIME | 120 ECTS

For whom?

Just graduated with a Bachelor Degree in clinical, public health or biomedical sciences and want to start making substantial contributions to future developments in medicine as a researcher? Then this Research Master is for you! With a wide range of specialisations and guidance from some of the greatest minds in these fields, you will be well on your way to a very successful research career.

If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

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Specialisations

  • Genetic Epidemiology
  • Epidemiology
  • Clinical Epidemiology
  • Public Health
  • Health Economic Analysis

Doctorate

PhD Programme | 4 Years | FULL-TIME

For whom?

This content of this programme will be published soon. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Pharmaco Epidemiology
  • Public Health

Postgraduate Programme | 1 Year | FULL-TIME

For whom?

Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

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Specialisations

  • Epidemiology
  • Clinical Epidemiology
  • Genetic Epidemiology
  • Public Health

Senior Advanced PhD Programme

For whom?

The content of this web page is currently under construction. Our apologies for the inconvenience. Please contact our office if you wish to receive further information about this programme.

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Specialisations

  • Clinical Epidemiology
  • Epidemiology
  • Genetic Epidemiology
  • Health Economic Analysis
  • Medical Psychology
  • Pharmaco Epidemiology

Executive Education

Executive Master of Science in Health Sciences | 2(+)years | Part-time | 70 ECTS

For whom?

This Executive Master programme focuses on training individuals who have already  authored scientific publications, but wish to take a step further in developing a successful career in health science research. The programme is ideal for working professionals since you can fully customize it to fit your busy schedule.

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Specialisations

  • Epidemiology
  • Genetic Epidemiology
  • Clinical Epidemiology
  • Pharmaco Epidemiology
  • Public Health
  • Medical Psychology
  • Biostatistics

Courses

28 Aug 2017 - 15 Sept 2017
Study Design [CC01]

About this course

In this course, the principles and practice of follow-up and case-control studies will be taught. The theory underlying the different design options will be discussed in depth. The course focuses on the classical approach but also addresses modern concepts. The practice of conducting follow-up and case-control studies with emphasis on issues of validity will be discussed. Lectures will be complemented by exercises using current examples of epidemiological studies.

Participants will be asked to work out a study design and prepare a formal presentation on the last course day.

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18 Sept 2017 - 13 Oct 2017
Biostatistical Methods I: Basic Principles [CC02]

About this course

The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Biostatistical Methods I: basic principles is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software package SPSS to work through exercises.

CC02 consists of two parts. In part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures. In part B, which last two weeks, more advanced methods will be discussed, including linear correlation and regression, multiple linear regression, analysis of covariance, regression diagnostics, stratified analysis and time-to-event analysis. The logistic regression model and the Cox proportional hazard regression model will be introduced briefly.

During the lectures, time will be spent on practical examples and exercises. SPSS will be introduced in the first week. Throughout the course, examples of SPSS-programmes and -output will be demonstrated in relation to the several topics that will be discussed.

Biostatistical Methods I: Basic Principles, part A (CC02A) is equivalent to Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22).

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18 Sept 2017 - 22 Sept 2017
Biostatistical Methods I: Basic Principles Part A [CC02A]

About this course

The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Biostatistical Methods I: Basic Principles is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software package SPSS to work through exercises.

In CC02 part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures.

During the lectures, time will be spent on practical examples and exercises. SPSS will be introduced. Throughout the course, examples of SPSS-programs and -output will be demonstrated in relation to the several topics that will be discussed.

The courses Introduction to Data-analysis (ESP03) and Biostatistics for Clinicians (EWP22) are equivalent to Biostatistical Methods I: basic principles, part A (CC02A).

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16 Oct 2017 - 20 Oct 2017
Clinical Translation of Epidemiology [CE01]

About this course

In the course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and data analysis and give a sufficient scientific and methodologic background to actively participate in clinical studies.

Topics are: principles of applied clinical research, diagnostic reasoning, diagnostic and prognostic research, comparative (clinical) experimental study, comparative non experimental study, meta-analysis and evidence based medicine.

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16 Oct 2017 - 17 Oct 2017
Linux for Scientists [GE14]

About this course

This course aims to teach users of a Linux/UNIX system how to work with the command line interface. After an introduction to some history and basic concepts the basic commands for file and directory manipulation will be discussed. Subsequently, the students will learn how to manage processes as well as input and output redirection, followed by more advanced text processing utilities like 'sed' and 'gawk'.

The second half of the course shows how to write Bash shell scripts to automate tasks. This knowledge is then used when discussing the Sun Grid Engine job queue system in use on the epib-genstat servers.

The course will focus on providing hands-on experience, so those who have been using a Linux system for a longer time will be able to skip the parts they already feel comfortable with and move on to more advanced concepts like regular expressions, version control and advanced use of a text editor. 

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16 Oct 2017 - 20 Oct 2017
Public Health Research: Analysis of Population Health [HS02a]

About this course

Public Health Research: From Epidemiology to Health Promotion
Module: Analysis of Population Health
This module aims to teach methods to assess the health of populations at national and local levels. Students are taught to calculate, apply and interpret population-based measures of mortality, quality of life and disease occurrence. In addition, students learn methods to assess time trends in population health (e.g. APC methods) and to analyse inequalities in health between social groups.

Note: HS02a, HS02b and HS02c will be tested after the HS02c course!

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18 Oct 2017 - 09 Nov 2017
Genetic-epidemiologic Research Methods [GE02]

About this course

The aim of this course is to introduce participants to the basic principles of genetic epidemiological research.The first part of the course is dedicated to binary traits, covering the basics of probability theory, hypothesis testing, risk calculation in families, and principles of complex segregation analysis. The second part of the course focuses on the genetics of quantitative traits, covering the concept and estimation of heritability and basic quantitative trait linkage analysis using modern genetic analysis software such as SOLAR and MERLIN. In the third part of the course design of genetic epidemiological studies will be discussed. This will be illustrated by practical examples and an assignment to develop a study.During the third week of the course, students will work in groups on this assignment, and will prepare a presentation.

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23 Oct 2017 - 27 Oct 2017
Public Health Research: Analysis of Determinants [HS02b]

About this course

Public Health Research: from Epidemiology to Health Promotion
Module: Analysis of Determinants
This module elaborates on research of the analysis of determinants of and inequalities in population health and risk factors of disease. Students will be introduced in:
- current insights in the main determinants of population health and risk factors of disease;
- determinants of inequalities in population health;
- research methods for the analysis of these determinants and
- challenges for future research in these issues.

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26 Oct 2017 - 07 Nov 2017
Clinical Epidemiology [CE02]

About this course

In clinical epidemiology, research focuses on questions of diagnosis, prognosis and etiology. To address these questions, several research options are available, including cohort studies and randomized controlled trials. Results from clinical epidemiologic research are used to inform clinical practice, both directly and by integrating the data in decision models, in order to make evidence-based and value-based clinical management decisions.

In this course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and to provide the required scientific and methodologic background to actively participate in clinical studies.

Topics are: principles of applied clinical research, diagnostic reasoning, diagnostic and prognostic research, comparative effectiveness, evidence based medicine, randomized controlled trials, protocols for clinical trials.

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30 Oct 2017 - 03 Nov 2017
Public Health Research: Intervention Development and Evaluation [HS02c]

About this course

Public Health Research: from Epidemiology to Health Promotion
Module: Intervention Development and Evaluation.
This module elaborates on the intervention development, implementation and evaluation phases in the model of planned promotion of public health.
Students will:
- be introduced to strategies and opportunities of primary and secondary prevention;
- learn how to work from determinants to interventions, i.e. how to translate determinants into intervention goals and intervention components and;
- learn about the opportunities and challenges of evaluation of primary and secondary prevention interventions and;
- be introduced to theory and challenges in dissemination of prevention interventions.

The course uses examples from health behaviour change, cancer screening, and vaccination.

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13 Nov 2017 - 17 Nov 2017
SNPs and Human Diseases [GE08]

About this course

The analysis of DNA polymorphisms, in particular Single Nucleotide Polymorphisms (SNPs), is becoming a standard research approach to understand causes of disease, in particular the so-called \"complex\" diseases such as diabetes, osteoporosis, cancer, etc. The aim of this course is to give a broad introduction in SNP techniques and applications. The course will deal with five main topics, which are in logical order:
- General Introduction and Study design,
- Bio informatic tools for SNP finding and analysis,
- Genotyping techniques and DNA management,
- Data analysis, and
- Examples of research in which SNPs are used.

Every day will cover one topic. The programme for every day will consist of four to six presentations, including international speakers, and there are learning-by-doing sessions. The possibility exists for participants to discuss their own data and work. This course is organized by the Molecular Medicine postgraduate school (MolMed) in collaboration with NIHES.
For more information check:
https://www.molmed.nl/

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13 Nov 2017 - 17 Nov 2017
International Comparison of Health Care Systems [HS03a]

About this course

Insight into the structure, process and outcome of health care systems is vital to be able to implement health care reforms that are effective in improving the health system performance. International comparisons of health care systems and the underlying political, organizational and financial arrangements are a multidisciplinary research field with a mixture of quantitative and qualitative methods. This course will present the various methodological approaches and will build on recent national and international experiences with comparative research.

The course starts with a clear conceptualization and definition of a health care system, definitions of key system components such as the service delivery system (through professionals and institutions), financing, role of the government and role of patients. Health system performance will be discussed in terms of effectiveness, equity and efficiency. Analytical perspectives taken will come from public health as well as from political sciences and economics. The course will also deal with the recent work performed by international organisations such as the WHO and OECD with respect to health system performance measurement and management.

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20 Nov 2017 - 08 Dec 2017
Biostatistical Methods II: Classical Regression Models [EP03]

About this course

The aim of this course is to introduce several important statistical regression models for non-normal and censored outcomes that are widely applied in clinical and epidemiological research. The course starts with a brief presentation of the basic principles behind likelihood theory, followed by a detailed discussion of logistic regression for dichotomous data, Poisson regression for count data, and closes with an extended presentation of regression models for time-to-event data, including the Cox proportional hazards model and the accelerated failure time model.
The course will be explanatory rather than mathematically rigorous, with emphasis given on application such that participants will obtain a clear view on the different modeling approaches, and how they should be used in practice.

To this end, the course includes several computer sessions during which participants will be asked to implement in practice the methods discussed in the theory sessions. Oral exam will be on two days: December 8 and 9, 2016

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22 Nov 2017 - 29 Jan 2018
Scientific Writing in English for Publication [SC07]

About this course

Course days in 2017-2018 will be:
Wednesday November 22, Wednesday December 13, Monday January 15 and 29.
The first 3 sessions will be on mornings or afternoons depending on your group. The last session on the 29th will be in the morning, afternoon or evening depending on your group and other course schedule.

Writing to be read
This course will focus on:
- Communicating the point and importance of your research;
- Writing a clear and readable scientific article.

The course consists of 4 half-day sessions and 3 writing assignments that will receive individual feedback from the instructor as well as other course participants. Attending all 4 sessions and completing all writing assignments is compulsory. The course will be intensive—writing takes time—so we suggest that participants reserve considerable time for this course.

Participants will be guided through the writing process in 3 assignments:
1. Clarifying the point of the research;
2. Completing the Hourglass Template with the main messages for the Introduction, Methods, Results, and Discussion of your research;
3. Writing the Abstract and Title.

Part of the work will be peer reviewing. Participants will critically discuss each of the three assignments with a peer-review partner (i.e. another course participant). The remaining members of the peer-review group will review and critique each assignment as well. This implies that participants must be willing to work closely with a peer-review partner during the course and meet deadlines for peer reviewing. After revising texts based on these reviews, participants then send them to the instructor, who will provide both substantive and language tips.

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22 Jan 2018 - 26 Jan 2018
Advanced Topics in Decision-making in Medicine [EWP02]

About this course

This course deals with advanced topics in clinical decision making. We will discuss a proactive systematic approach to decision making in health care and review the principles of cost-effectiveness analysis. Special topics that will be addressed include problems with utility assessment and multi-attribute utility theory, cost-analysis, modeling issues, Markov process models, Monte Carlo simulation modeling, and Value of Information analysis. The course will consist of lectures in the morning and a computer practicum in the afternoon.

During the week you will be given the opportunity to work on an own case example. Think of a decision problem that you are currently involved in or were recently confronted with. It may be a clinical decision problem involving a patient you care for, a management decision problem you are struggling with, a public health policy problem you are involved with, or a personal (preferably medical) decision problem. It must, however, be something you are willing to talk about in class and are motivated to work on.

Teaching Methods
9:00-12:00: Interactive lectures
13:00-16:00: Computer lab: Computer assignments and work on own case example with help from teaching assistants and the lecturer.

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12 Feb 2018 - 16 Feb 2018
Principles in Causal Inference [EP01]

About this course

Epidemiologic research often entails asking and trying to answer questions toward understanding the causes and consequences of health outcomes. Answers to such causal questions require us to combine data (e.g., from observational studies) with assumptions to estimate causal effects. This course will teach students to think critically and rigorously about the implications of study design and analysis toward addressing such causal questions. Students will learn formal causal inference \"languages\" – including the concept of a target trial, causal diagrams, and counterfactual theory – to articulate research questions, inform an analytic approach, and identify threats to validity such as confounding.

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Erasmus Winter Programme (EWP)

For more information about the Erasmus Winter Programme (EWP), please go to:

See overview of all available courses