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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.nlMaster
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.
Read MoreMaster 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.
Read MoreResearch 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.
Read MoreCourses
02 Jun 2025 - 06 Jun 2025
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.
03 Feb 2025 - 07 Feb 2025
Using R for Decision Modeling in Health Technology Assessment [EL005]
About this course
This course aims to teach how to build decision models in R to students who have an understanding of health decision science.
- The course combines lectures with R coding exercise.
- The course is project-based. You are expected to apply the theory and skills you learn during this course to a decision problem you select yourself.
- The assignments in this course are group work.
Important: this course has a pre-course preparation module with a workload of 4-10 hours, which you must finalize prior to the course.
More detailed information about each session will be provided in the syllabus.
Attendance of all lectures and practicums is compulsory in order to be able to complete the assignments and case example successfully. Each day builds on knowledge and skills from the previous day. Clarification of the material taught is best done in the interactive teaching environment provided during classroom sessions.
See 'how to apply' for the course registration period.
Read More03 Mar 2025 - 07 Mar 2025
An Introduction to the Analysis of the Next-generation Sequencing Data [EL019]
About this course
This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.Subjects that will be covered include:
- NGS: an introduction to methodology and techniques;
- Basic statistics of NGS data, e.g. coverage;
- Aligning the sequence reads;
- Calling sequence and structural variants;
- Dealing with various file formats (samtools, VCFtools, GATK);
- Annotating sequence and structural variants;
- Evaluating functional effects of the genetic variants on proteins;
- Conversion to other formats;
- Single variant and Collapsed genotype analyses with various tools (e.g. seqMeta, RAREMETAL and RVtest);
- Finding variants with recessive effects and compound heterozygosity;
- Search for rare variants in families and population based studies for complex phenotypes;
- Search for rare variants in Mendelian disorders, and
- Imputation of sequence variants.
See 'how to apply' for the course registration period.
03 Mar 2025 - 12 Mar 2025
Public Health Across the Life Course [EL024]
About this course
From prenatal to old age, each phase in life is characterized by specific public health challenges. Life-course epidemiology increasingly shows how health problems at one or multiple periods in life have consequences for public health later in life. Preventing immediate or later life consequences requires appropriate public health strategies. In this course, these strategies are pivotal; students will be trained how and why public health strategies in different phases of the life course are developed and implemented. The core theme of the course is how to use epidemiological evidence for public health strategies implemented in society. Application of the research methods will be illustrated with existing strategies concerning prenatal care, early child development, labour participation, ageing and end-of-life care.
The programme consists of lectures, group discussions and an assignment.
See 'how to apply' for the course registration period.
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.
Read More07 Apr 2025 - 11 Apr 2025
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.
Read More07 May 2025 - 09 May 2025
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.
Read More07 May 2025 - 16 May 2025
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.
Read More09 Apr 2025 - 11 Apr 2025
Advanced Analysis of Prognosis Studies [EL014]
About this course
Prognostic models are increasingly published in the medical literature each year. But are the results relevant for clinical practice? What are the critical elements of a well developed prognostic model? How can we assume that the model makes accurate predictions for our patients, and not only for the sample that was used to develop the model (generalizability, or external validity)?
In the course we will address these and other questions from a methodological perspective, using examples from the clinical literature.The participants will be encouraged to participate in interactive discussions and in practical computer exercises.
See 'how to apply' for the course registration period.
Read More10 Feb 2025 - 14 Feb 2025
The Placebo Effect [EL028]
About this course
This course is cancelled in 2023. We hope to offer it again in the spring of 2024.
The placebo effect has been studied since the 1950’s, starting with the original 1955 study of Beecher. In this course we will discuss several postulated underlying mechanisms of the placebo effect (e.g. expectancy, conditioning, affect-modulation, and doctor-patient communication). Furthermore we will debate the existence of the placebo effect and discuss the challenges in measuring the effect. Questions that will be addressed are for instance: can you deliver an open label placebo? Is it ethical to prescribe a placebo when a patient doesn’t know he is getting a sugar pill? Does the placebo effect exist outside of pain medication research? You will experience the strength of the placebo effect first hand in an experiment during the course.
The assessment of the course will exist of the presentation of a research proposal for studying the placebo effect.
See 'how to apply' for the course registration period.
Read More10 Feb 2025 - 14 Feb 2025
Qualitative Research Methods in Medicine [EL030]
About this course
Qualitative research is becoming more prominent in medicine and health care. In this 5-day course, students will be introduced to the basic principles of qualitative research methods in medicine. Students will be equipped with the necessary knowledge and skills to design, conduct and report on qualitative research. In addition, the basic principles of data-analysis using the qualitative data analysis program NVivo will be taught.
See 'how to apply' for the course registration period.
Read More10 Mar 2025 - 14 Mar 2025
Advanced Clinical Trials [EL013]
About this course
The Randomized Controlled Clinical Trial (RCT) is the most reliable method of assessing the efficacy and effectiveness of interventions. In order to provide the best possible evidence-based health care, health professionals must be able to judge the scientific merits and clinical relevance of published RCTs. In addition, they may be involved in designing and performing a RCT and are frequently asked to recruit patients for RCTs.
Reports published in major medical journals show a surprising variability in methods including choice of study design, blinding, avoidance of bias, outcome measures, effect parameters, sample size calculations, data analysis techniques, presentation of results in tables and figures, and inferences made from the results. Hence, appraising trial reports can be challenging. In designing RCTs many difficult decisions need to be made with respect to these same issues.
In this course these topics and issues will be addressed and developed through lectures and group practical sessions. A laptop during classroom sessions is required in order to do the practical assignments.
See 'how to apply' for the course registration period.
12 May 2025 - 16 May 2025
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.
Read More12 May 2025 - 16 May 2025
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.
Read More14 Apr 2025 - 16 Apr 2025
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.
Read More17 Feb 2025 - 19 Feb 2025
Mendelian Randomisation [EL018]
About this course
With the advent of a very large number of genetic databases and resources, opportunities to conduct Mendelian randomization(MR) studies are quickly increasing. The MR approach proposes using genetic variants as instrumental variables to test or estimate the potential causal effect of a (non-genetic) risk factor on a disease or health-related outcome. When the assumptions are met, the MR approach can overcome the limitations of associations drawn from observational epidemiology and help prioritizing potential targets for pharmaceutical and public health interventions. This 3-day course aims to provide all the tools necessary first to understand the basic principles of causal inference underlying MR and second to perform an MR study; covering both simple and complex statistical methods for causal inference within one- and two- sample Mendelian randomisation frameworks. During the first day, basic principles of causal inference and mediation analysis will be covered. On the second day, students will apply the concepts learned on day 1 within a Mendelian randomisation framework; including methods to assess instrumental variable assumptions and working on hands-on practical sessions employing online tools like MR-base, but also using specific R-libraries. During day 3, examples of published MR studies will be presented followed by discussion of the topics and a short Q&A session. In addition, students will be able to run specific hands-on analyses with diverse summary level datasets. While theoretical background is provided on all topics, this is by definition a "hands-on" practical course, meaning you will spend most of the day performing MR analyses." Starting this year, the EL018 course will be given on a yearly basis.
See 'how to apply' for the course registration period.
Read More18 Feb 2025 - 27 May 2025
Scientific Writing in English for Publication [LLS01]
About this course
This course is designed to help you become aware of what it is that makes texts work, and it will help you apply this knowledge in practice. During the course you will be working on the different sections of your own research paper. You will also receive feedback from your peers and instructor. By the end, you will have a draft which you can use to develop your research paper further.
The course starts with two sessions by professor Arfan Ikram and professor Frank Wolters in Februari. Additionally there are 5 sets of 5 dates available for this course.
19 May 2025 - 28 May 2025
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.
Read More19 May 2025 - 23 May 2025
Operations Management [EL035]
About this course
Operations management is concerned with evaluating the performance of operating units, understanding why they perform as they do, designing new or improved operating procedures and systems for competitive advantage, making short-run and long-run decisions that affect operations, and managing the work force. To understand the role of operations in any organization, a manager must understand process analysis, capacity analysis, types of processes, productivity analysis, development and use of quality standards, and the role of operating strategy in corporate strategy. The course will also present the focused management approach which can help an organization achieve much more with existing resources. The course will demonstrate how operations management—in particular Lean and the Theory of Constraints (TOC)—can rapidly advance value and performance in any health care organization. Utilizing a systems approach that will be relevant for health care managers and executives, it unpacks and demystifies concepts such as performance measures, operations, quality, cost accounting, pricing, and value enhancement, all as they relate to eliminating waste and non-value-adding activities.
See 'how to apply' for the course registration period.
Read More20 Jan 2025 - 22 Jan 2025
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.
Read More23 Jan 2025 - 24 Jan 2025
Linux for Scientists [EL016]
About this course
In this course, students will learn how to work with the command line interface of a (remote) computer running a Linux/UNIX operating system. Many scientists in, for example, the fields of genetic epidemiology, bioinformatics and machine learning run large analyses on Linux servers and many software packages and pipelines are developed only for Linux.
After an introduction to some history and basic concepts, students will learn how to find their way around the system and several commands for file and directory manipulation will be discussed. Subsequently, we will cover how to edit files on the server as well as how to redirect input and output of commands and how to use this to create pipelines. At the end of day one, this is followed by the use of more advanced text processing utilities like 'sed' and 'awk'.
The second day of the course teaches 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 for example 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.
23 Apr 2025 - 25 Apr 2025
Causal Thinking [EL036]
About this course
This course is intended to supplement and build on the training in causal inference received by NIHES students in CK010: Study Design and ESP48: Causal Inference. A student taking all 3 of these courses will have seen all important topics in causal inference. Additionally, we will take a closer look at the assumptions that underlie all the most commonly used ways to estimate causal effects (confounder control, instrumental variable analysis, regression discontinuity and differences in differences) emphasizing a deeper intuition for why they are needed. We will also go deeper into concepts such as bias analysis and triangulation. This course will use counterfactual notation and basic concepts in logic and probability. Students will be evaluated based on a group project where they use triangulation in a real, applied example.
Read More24 Feb 2025 - 26 Feb 2025
Child Psychiatric Epidemiology [EL011]
About this course
Psychiatric problems frequently occur in children and adolescents. Epidemiological methods are used in child psychiatric research to study the occurrence of psychiatric disorders, test causal hypotheses and investigate the developmental trajectories.
In this course epidemiological research and methods in Child and Adolescent Psychiatry will be discussed in depth. Using an interactive approach most material is presented in seminar format. A wide range of topics will be covered ranging from descriptive epidemiology, major research milestones, current methodological challenges to a future research agenda for Child and Adolescent Psychiatry. These themes are linked to selected major disorders. Other seminars will cover selected research topics. Students are engaged to evaluate and design different research projects. Particular emphasis lies on study designs with a developmental, multi-informant, or multi-method approach.
Read More27 Jan 2025 - 31 Jan 2025
Topics in Medical Decision Making [EL004]
About this course
This course deals with intermediate- to advanced level topics in the field of medical decision making. Topics that will be addressed include building decision models, evaluation of diagnostic tests, utility assessment, multi-attribute utility theory, Markov cohort models, microsimulation state-transition models, calibration and validation of models, probabilistic sensitivity analysis, value of information analysis, and behavioral decision making. The course will focus on the practical application of techniques and will include published examples and a computer practicum. Students will learn to apply state-of-the-art modeling methods using freely available open source software to evaluate the comparative effectiveness and cost-effectiveness of health interventions. While the primary emphasis is on application, essential underlying theoretical concepts will also be discussed. During the course you will have the opportunity to work on a decision problem which you select yourself. Many students use the course as a way to start writing a paper on a decision model in the field of their interest.
Note that this is an intensive course. Be prepared to spend at least 5 days, 8 hours per day on the course. You cannot expect to do other time-consuming commitments while doing this course.
See 'how to apply' for the course registration period.
Read More27 Jan 2025 - 31 Jan 2025
Introduction to Genome-Wide Association Studies [EL017]
About this course
This 5-day introductory course aims to give an overview of the field of Genome Wide Association Studies (GWAS). During the first half of the course we focus on the biological knowledge required to understand GWAS as well as the design of GWAS studies and basic skills required to perform GWAS. In the second half of the course you will perform a GWAS as well as post-GWAS analyses to help you understand the field as a whole. GWAS is a skill one can only master by practice, which is why we give you ample opportunity to practice what we have taught you and learn the skills needed to perform your own GWAS.
See 'how to apply' for the course registration period.
Read More31 Mar 2025 - 04 Apr 2025
Advanced Decision Modeling [EL006]
About this course
This week-long, project-based course aims to provide students with an understanding of advanced methods used in decision-analytic modeling and cost-effectiveness analyses. These include topics like the latest methods for calibration and validation, quantifying uncertainty, and consideration of heterogeneity of patient benefits and equity issues. The course combines lectures and readings to give theoretical foundation and perspectives with in depth project work and presentations to give practical concrete understanding in a way that furthers students’ specific research goals.
Course Structure:
Each day will begin with a lecture by Professor Goldhaber-Fiebert on an advanced methods topic. After the lecture, lab sessions will commence with students working on their projects as Professor Goldhaber-Fiebert circulates through the room and students assist each other in a collaborative environment. Most days Professor Goldhaber-Fiebert will also give an afternoon lecture. In addition, at the end of days 2, 3, and 4, Professor Goldhaber-Fiebert will give an additional, shorter, informal lecture (i.e., "a chalk talk") on a methods topic tailored to specific issues that are arising within students’ projects. Additionally, throughout the week, Professor Goldhaber-Fiebert will have one-on-one meetings with students about their projects.
See 'how to apply' for the course registration period.
Read More