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Programme overview (based on your choices)

Majors

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 EC points

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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  • Epidemiology
  • Clinical Epidemiology
  • Public Health Epidemiology
  • Biostatistics
  • Health Decision Sciences
  • Genomic & Molecular Epidemiology
  • Master of Science in Health Sciences | 2(+)years | Part-time | 70 EC points

    For whom?

    This world-class programme is ideal for the working health professional, who wishes to take a step further in developing a successful career in health science research. The programme can be fully customized to fulfill your professional and personal aspirations and fit your busy schedule.

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  • Epidemiology
  • Clinical Epidemiology
  • Public Health Epidemiology
  • Biostatistics
  • Health Decision Sciences
  • Genomic & Molecular Epidemiology
  • Research Master in Health Sciences | 2 Years | FULL-TIME | 120 EC points

    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 majors 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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  • Epidemiology
  • Clinical Epidemiology
  • Public Health Epidemiology
  • Biostatistics
  • Health Decision Sciences
  • Genomic & Molecular Epidemiology
  • Courses

    02 Sept 2024 - 27 Sept 2024
    Review of Mathematics and Introduction to Statistics [CK001]

    About this course

    Several courses in the NIHES curriculum require a good working knowledge of basic concepts in mathematics and statistics. These courses include Biostatistics I (CK020), Biostatistics II (CK030), Repeated Measurements (EL002) and Bayesian Statistics (EL003). The course Review of Mathematics and Introduction to Statistics aims to prepare you for these statistical courses by helping you to obtain a sufficient working knowledge of mathematics and statistics.

    This course is a self-study course based on online material (videos from external sources) and the material in an accompanying reader. A Q&A session will be organized near the final course deadline, and the organizers of the course are available for questions during the course. There will be no lectures or tutorials aside from the Q&A. A number of exercises and a practice test are included in the course materials.

    The content of this course is divided into the following topics:

    • Basic mathematical operations
    • Functions
    • Differentiation
    • Optimization
    • Integration
    • Vectors and matrices
    • Basic concepts in statistics

    This course was previously registered under the course code BST01.

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    02 Dec 2024 - 13 Dec 2024
    Principles of Public Health [CK050]

    About this course

    Life expectancy increased in the past decades, but will this remain to be the case? While public health strategies contributed to improvements in population health, major challenges remain. Improving population health in the next decade(s) requires a thorough analysis of current challenges, their causes and solutions. In this course, students will learn the concepts and methods for an analysis of the health of the population, the identification of the main causes, and the evaluation of strategies to improve population health. Summary measures of population health and the impact of diseases on population health will be start of the course, followed by a life course perspective on multilevel determinants of health. Variations in health will be investigated with mediation analysis. Students will also be introduced in mixed method approaches for the evaluation of public health strategies, including natural experiments.

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.


    You can view a view examples of the group assigment here

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    04 Nov 2024 - 15 Nov 2024
    Science Communication [LLS12]

    About this course

    As a researcher, you will be trained to communicate your research findings to colleagues by means of a poster, a conference talk, or a scientific publication. But fellow scientists are not the only target group for our results: we often want to further disseminate our findings. Are we well equipped to communicate our research findings to a wider audience and what does it take to do this properly? In four half-day sessions we will explore some of the basic principles of science communication. In the lectures we will discuss topics such as what is meant by societal impact, how to determine the target group of your research and how to communicate to different audiences. In subsequent interactive sessions, you will implement the gained knowledge in several exercises using your own research.

    The live sessions for this course will take place on:
    Monday 6 November
    Friday 10 November
    Monday 13 November
    Friday 17 November

    The assessment consists of:


    - Attendance and professional conduct;
    - Preparatory assignments;
    - Final assignment: creating a pitch video.

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    04 Nov 2024 - 02 Dec 2024
    Networking & Influencing Skills [LLS14]

    About this course

    How do you get things done in such a complex organization as the Erasmus MC? As in any big organization there are formal procedures and informal channels. In this one day course you will get a better view of your political arena and the players in your field. You will understand your own challenges and you will be invited to step out of your comfort zone to make the impact you deserve. Body language, tone, voice, tempo and bearing discomfort are needed to increase your visibility. At the end of the day you will know who to approach, and how, to make the first step in achieving your goal.

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    06 Jan 2025 - 17 Jan 2025
    Selected Topics in Epidemiology [CK060]

    About this course

    This course focusses on the application of the theoretical concepts, that students have thus far learned in the previous courses of the core curriculum, to health-related topics. After having learned the principles of research methods, study designs, and statistical analyses, it is equally important to learn how to effectively apply these concepts in "real-life" settings. To improve population health, theoretical background needs to be complemented with applied epidemiological competencies. In this course, we will retain the established and novel didactics of epidemiology with an overlay that prepares the students to work on specific health-related topics. The overall aim of this course is to teach students how the theoretical concepts appear in real-life settings (sometimes presented using different terminologies).

    The course includes a wide range of domains:

    • Infectious disease epidemiology (Prof.dr. S.J. de Vlas);
    • Medical psychology (Prof.dr. J.J. van Busschbach);
    • Health technology assessment (Dr. B.S. Ferket);
    • Pharmaco-epidemiology (Prof.dr. B.H.C. Stricker);
    • Psychiatric epidemiology (Dr. A.I. Luik);
    • Lifestyle epidemiology (Dr. R.G. Voortman);
    • Genomic and molecular epidemiology (Prof.dr. F. Rivadeneira);
    • Big data (Prof.dr. D. Rizopoulos).

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.

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    06 Sept 2024 - 30 Jun 2025
    Intervision [LLS05]

    About this course

    Intervision is a method to collaboratively analyse the experiences you (have) come across during your research project and study programme in a practical and systematic way, together with your peers. This analyses leads to solutions, alternatives and advice, and will often also give you more insight into your own functioning.

    Examples of experiences you can discuss during the intervision are: experiences during your research phase (e.g. dealing with hierarchy or work load), personal experiences (e.g. giving presentations), succes experiences (e.g. something you were not looking forward to went very well), or other experiences.

    The intervision sessions serve two purposes: they are meant to teach you reflective skills, and to help you work on solutions to problems you have faced or are facing during your research project and study programme.

    The intervision course consists of 4 meetings (1-2 hours each) spread out through the year, with an introductory meeting in September.

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    07 Oct 2024 - 11 Oct 2024
    The Body-Mind Connection [LLS09]

    About this course

    During this course we will explore how the evidence-informed practice of embodied awareness can be beneficial to increase resilience and prevent burnout. The healthcare environment can be challenging and demanding, causing a feeling of pressure and stress. This can lead to physical and emotional fatigue, disengagement, feelings of reduced accomplishment, and a myriad of physical ailments – these are signs and symptoms of burnout. We know the problem is caused by both organizational and individual factors and that a systems approach is necessary. We also know that developing your own personal skills gives you more agency over your own wellbeing. In this course you will learn skills you already have but that are undervalued in the rationality of our current society.

    You will leave with insight into your own reaction patterns through experiential learning. You will develop practical skills to take better care of yourself and stay more balanced. The tools will help you to stay clear headed, calm and focused while making critical decisions and having to perform under pressure.

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    09 Sept 2024 - 27 Sept 2024
    Study Design [CK010]

    About this course

    In this course, the principles and practice of cohort and case-control studies will be taught as well as the important topics underlying epidemiologic studies such as validity and precision. The theory underlying the different design options and concepts will be discussed in depth using causal inference and counterfactuals. Also, a historical perspective on causal thinking will be presented. The course focuses on the classical approach but also addresses modern concepts. 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 in the last week of the course.

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of a presentation. The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the presentation during the course is mandatory for all participating students.

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    10 Jun 2024 - 12 Jun 2024
    Cardiovascular Epidemiology [EL010]

    About this course

    Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. The overall objective of the cardiovascular epidemiology course is to produce epidemiologists and other health scientists with the essential knowledge to carry out high quality research in cardiovascular disease.

    See 'how to apply' for the course registration period.

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    10 Jun 2024 - 14 Jun 2024
    Psychopharmacology [EL029]

    About this course

    More than one billion people worldwide are living with a mental or addictive disorder, making them both leading causes of disability and a significant risk factor for premature mortality (Arias et al. (2022) eClinicalMedicine). Treatment of mental disorders usually involves drug therapy, psychotherapy, or a combination of both. Psychopharmacology, the topic of this course, is the scientific study of the effects drugs have on mood, sensation, thinking, and behavior. In this crash course on psychopharmacology, we will look at drug treatment for psychiatric disorders such as depression, anxiety and ADHD. How do these (psychoactive) drugs work? How and why do they invariably lead to side-effects? And how do these side-effect affect adherence?

    To answer these questions, we should strive to become a ‘neurobiologically empowered psychopharmacologist’, according to the renowned psychopharmacologist Dr. Stephen Stahl. In this course we therefore aim to give you at least a basic understanding of the underlying neurobiology of anxiety, depression, ADHD, addiction and cognition.

    As a final topic, to explain how the most effective drug dose for one person can be either ineffective or dangerous for somebody else, we will also cover both pharmacokinetics (how our bodies interact with the drugs we take) and pharmacogenetics, the study of the effect of genomic variations on drug response.

    See 'how to apply' for the course registration period.

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    13 May 2024 - 17 May 2024
    Introduction to the Analysis of Population Proteomics & Metabolomics [EL020]

    About this course

    This course aims to give an introduction to the analysis of proteomics and metabolomics data, two emerging approaches that help better understanding of molecular pathways and promise identification of novel biomarkers for complex diseases. The course offers an excellent introduction to these ‘omic’ topics and gives the opportunity to analyse example datasets.

    The course targets a wide-range of participants, including students, epidemiologists, clinicians and molecular biologists with little background in genetic epidemiology. Participants are introduced to the basic principles of protein and metabolite profiling and association analyses at population level. The relevant background of genetic epidemiology and statistics is presented.

    The course consists of two parts: theoretical lectures and practical assignments. The goal of the course is that participants are able to analyze and interpret the findings in modern population genetic and genomic research.

    See 'how to apply' for the course registration period.

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    13 May 2024 - 15 May 2024
    Quality of Life Measurement [EL023]

    About this course

    In recent years, the patient's assessment of quality of life has developed to an important outcome measure in epidemiology and health services research. Moreover, quality of life measures are increasingly used as criteria in reimbursement policy, most notably in QALY-analysis.

    The aim of the course is to provide the participants first, with a review of the instruments currently available; Second, participants are provided with the knowledge required to select measures of quality of life that are both valid and sensitive for the research objectives of the participants;

    Third, participants will acquire the knowledge and practical skills necessary to adjust standard measures of quality of life instruments for their specific disease area’s, with a special focus on reimbursement. The programme consists of presentations, exercises and demonstrations of practical issues. Participants are invited to email their specific interest at forehand, and these topic will be discussed during the course.

    Programme:

    • Background of ‘health status' and ‘quality of life’.
    • Main principles of construction of a quality of life questionnaire.
    • Available instruments.

    Application.

    • Adaptation instruments for specific research questions: increase sensitivity.
    • QALY-analysis.
    • Practical and ethical value of measuring quality of life in a reimbursement setting.

    A facultative pre-course virtual welcome reception will be hosted on the Friday before the official start of the course. We highly recommend you attend this event as well!

    See 'how to apply' for the course registration period.

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    13 May 2024 - 17 May 2024
    Introduction to the Analysis of Population Epigenomics & Transcriptomics [EL034]

    About this course

    This course aims to give an introduction into the analysis and interpretation of epigenomics and transcriptomics data in the setting of population-based studies. We will introduce both types of omics and discuss their technical background, quality control and normalization, analytical approaches, interpretation of results and follow-up analyses.

    The course will include short practical sessions during which course participants can learn to with epigenomic and transcriptomic data using R.

    See 'how to apply' for the course registration period.

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    15 Apr 2024 - 19 Apr 2024
    Psychiatric Epidemiology [EL008]

    About this course

    This four-day course focuses on the principles and practice of psychiatric epidemiology. Basic concepts and issues that are specific to psychiatric epidemiology are covered. We will cover a range of psychiatric disorders such as depression, anxiety and sleep disorders and research approaches such as genetics and imaging to illustrate concepts and practice of psychiatric epidemiology. These topics will be covered by speakers from across the field.


    See 'how to apply' for the course registration period.

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    15 Apr 2024 - 19 Apr 2024
    Planning and Evaluation of Screening [EL022]

    About this course

    This course focuses on the design and the evaluation of health care programmes for the early detection of disease or screening. Screening takes place in a population without symptoms of the disease. The screening test characteristics have consequences for the favourable (improvement of prognosis by early detection, life years saved and deaths prevented) and unfavourable (overdiagnosis, unnecessary treatments) effects of screening.


    There are a number of designs for the assessment of the effectiveness of screening, such as randomized-controlled trials, observational prospective studies and case control studies. The pros and cons of each of these designs will be discussed. Evaluation methodologies, such as cost-effectiveness, cost-utility and technology assessment will be explained, including the concepts of quality adjustment of life years and of time preference. Detailed case studies include cervical, breast and prostate cancer screening, genetic screening, youth health care and screening for tuberculosis, e.g. for high risk groups. Several computer aids for the evaluation of screening are presented.

    Only the afternoon sessions require physical presence.

    See 'how to apply' for the course registration period.

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    18 Nov 2024 - 29 Nov 2024
    Clinical Epidemiology [CK040]

    About this course

    Research questions in clinical epidemiology originate from clinical practice. Caring for patients commonly triggers the research-minded clinician to question his/her knowledge and decisions. Questions may revolve around risk factors, prevention, diagnosis, prognosis and/or interventions leading to research studies. Results from clinical epidemiological research are used in patient management decisions. Understanding the research results, recognizing the limitations, and knowing how to apply them are essential to translate clinical research results to application in day-to-day clinical practice.

    In this course, the principles and practice of clinical epidemiology and the application of the results to clinical decision making will be discussed, using examples from the literature and from ongoing studies. The course is divided into 3 parts:

    1. Diagnosis
    2. Prognosis
    3. Interventions
    We use blended learning: a combination of video’s, readings, assignments, question-and-answer sessions, interactive lectures, and workshops.

    The assignments involve performing calculations. For the Diagnosis part we work with Excel. For the Prognosis part you will be using R code that has been written for you. To benefit maximally from this course we advise you to do the introduction to R - online course: install R and R Studio, learn basic R syntax, and learn basic R studio functionality. The DataCamp course Introduction to R is very helpful: https://www.datacamp.com/courses/free-introduction-to-r. The full DataCamp course will be available for course participants.

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.


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    24 Apr 2024 - 26 Apr 2024
    Competing Risks and Multi-State Models [EL001]

    About this course

    Competing risks and multi-state models play an increasingly important role in the analysis of time to event data. Regarding competing risks, there is a lot of confusion regarding the proper analysis. The most important reason for the confusion is conceptual: which quantities can be estimated and what do they represent. Once the concepts are understood and the proper type of analysis has been chosen, most analyses are straightforward and can be performed with standard software for survival analysis. For multi-state models with exactly observed transition times, estimation is reasonably straightforward and the real challenge is in (dynamic) prediction.

    The overarching goal of the course is to provide a solid introduction to these topics and thereby increase the analytical validity in this field.

    In the first part of the course we cover competing risks analysis: what are competing risks and when do we need to take them into account; the independence assumption; cause-specific cumulative incidence; cause-specific hazard and subdistribution hazard; competing risks as a multi-state model. We will also cover regression models on both cause-specific and subdistribution hazard (Fine-Gray model) and discuss the difference in interpretation. We show how analyses can be performed with standard software. In the second part of the course, the extension to multi-state models is discussed. The course will cover topics including transition intensities and transition probabilities, nonparametric estimation and regression models, as well as methods to obtain predictions of future events, given the event history and clinical characteristics of a patient. With right censored and/or left truncated data, we show that it is possible to perform many types of analyses using standard software, using the same techniques as in multi-state representation of the competing risks model.

    See 'how to apply' for the course registration period.

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    27 May 2024 - 07 Jun 2024
    Missing Values in Clinical Research [EL009]

    About this course

    Missing data frequently occur in clinical trials as well as observational studies. An important source for missing data are patients who leave the study prematurely, so-called dropouts. Alternatively, intermittent missing data might occur as well.


    When patients are evaluated only once under treatment, then the presence of dropouts makes it hard to comply with the intention-to-treat (ITT) principle. However, when repeated measurements are taken then one can make use of the observed portion of the data to retrieve information on dropouts. Generally, commonly used methods to analyse incomplete data include complete-case (CC) analysis and, in longitudinal studies, an analysis using the last observation carried forward (LOCF). However, these methods rest on strong and unverifiable assumptions about the missing mechanism. Over the last decades, a number of analysis methods have been suggested, providing a valid estimate for, e.g., the treatment effect under less restrictive assumptions.


    The assumptions regarding the dropout mechanism have been classified by Rubin and co-workers as: missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR).


    In the first part of the course we will review various repeated measurements models and indicate under which missing data mechanism they will provide valid estimates of the treatment effect. Finally, since it is impossible to verify that the dropout mechanism is MAR we argue that, to evaluate the robustness of the conclusion, a sensitivity analysis thereby varying the assumption on the dropout mechanism should become a standard procedure when analyzing the results of a clinical trial.


    The second part of the course focuses on multiple imputation (MI), specifically the fully conditional specification (FCS, MICE), which is often considered the gold standard to handle missing data. We will discuss in detail what MI(CE) does, which assumptions need to be met in order for it to perform well, and alternative imputation approaches for settings where MICE is not optimal. The theoretic considerations will be accompanied by demonstrations and short practical sessions in R, and a workflow for doing MI using the R package mice will be proposed.


    Examination for this course consists of two assignments.

    See 'how to apply' for the course registration period.

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    28 Oct 2024 - 15 Nov 2024
    Biostatistics II [CK030]

    About this course

    This course is offered in a hybrid setting, which means students can join the live lectures in class and online simultaneously.


    This course presents statistical regressions models for the analysis of dichotomous, count, and time-to-event data. In the first part, the course builds upon the introductory presentation of logistic regression from the Biostatistics I course and shows some of its extensions, including the conditional logistic regression model. The course then introduces regression models for the analysis of count data. The last part focuses on the statistical analysis of time-to-event data, starting from simple statistical tests and followed by the presentation of accelerated failure time and Cox proportional hazards models. For each modeling framework, a detailed discussion is given on how to build the model to answer the scientific questions of interest, estimate the model’s parameters, assess its assumptions, and finally, interpret the results of the analysis.

    The course will be explanatory rather than mathematically rigorous, emphasizing application such that participants will obtain a clear view of 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 learn to work with the R statistical language and implement the methods discussed in the theory sessions.

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.

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    29 May 2024 - 07 Jun 2024
    Sustainable Public Health [EL025]

    About this course

    In the ‘2030 Agenda for sustainable development’, the United Nations described 17 Sustainable Development Goals (SDGs), including interrelated goals on poverty reduction, population health, the living environment, and climate change. Achieving these goals requires multidisciplinary and international collaboration, in which public health experts also need to play an important role. This course is focussed on three important questions: What is the evidence for these connections, which public health interventions can synergistically work towards a sustainable future, and how to advise local or national governments best about this? Although priorities differ between countries, these questions are universal.

    The programme consists of ‘capita selected lectures’, lectures and training in valorisation, and a group exercise.

    See 'how to apply' for the course registration period.

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    30 Sept 2024 - 18 Oct 2024
    Biostatistics I [CK020]

    About this course

    This course is offered in a hybrid setting, which means students can join the live lecture in class and online simultaneously.

    This course provides an introduction to the basic concepts and techniques of statistical data analysis. The course starts with a presentation of fundamental notions of statistics and statistical inference under uncertainty. The course then continues with an in-depth presentation of classical regression models, namely, linear regression for continuous data, logistic regression for dichotomous data. Classical statistical parameter and non-parametric statistical tests are linked to these models. For each modeling framework, a detailed discussion is given on how to build the model to answer the scientific questions of interest, estimate the model’s parameters, assess its assumptions, and finally, interpret the results of the analysis.

    The course will be explanatory rather than mathematically rigorous, emphasizing application such that participants will obtain a clear view of 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 learn to work with the R statistical language and implement the methods discussed in the theory sessions.

    For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.

    Read More

    31 Oct 2024 - 28 Nov 2024
    Negotiation Skills [LLS13]

    About this course

    We negotiate every day: with our partners, children and colleagues. When it comes to negotiating for a better position or salary for ourselves, discomfort increases. This one day course clarifies the different mechanisms at play during a negotiation. The course will be a combination of theory and practice. You will get the tools how to stand your ground, bear discomfort and be open to the other person’s perspective. At the end of the day you will understand the mechanisms, see opportunities for negotiation and you will have gained the courage to take the next step. Prior to the course you are asked to fill out a questionnaire concerning your present negotiating skills.

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