Upcoming Events

The Scientist and the Storyteller Workshop is a two-day intensive training using a hands-on, workshop format that will equip scientists and journalists with concepts, tools, and strategies to successfully communicate scientific findings to the public. This two-day intensive workshop will help bridge the gap between scientific research findings and the distribution of important health information to the public. Led by a cross-disciplinary team of experts consisting of an experienced journalist and experienced public health researcher, the workshop will integrate seminar lectures with hands-on activities to put concepts into practice. This short course will train scientists to be better communicators and journalists to be better translators of scientific information. Participants will learn how science journalists work, how scientists are trained to report their findings, and best practices for collaboration between the two disciplines. By the end of the workshop, participants will be familiar with the following topics: What is journalism and how does it work? Newsworthiness The parts of a story Reporting Finding an angle Science writing vs journalism The language of reporters Translating research Writing your story Working better with journalists Audience and Requirements Scientists and journalists at all career stages are welcome to attend, and we particularly encourage trainees and early-career professionals to participate. Instructors Julie Herbstman, MSc, PhD, Columbia University.  Duy Linh Tu, Columbia Journalism School, Columbia University.  Additional Information Register for the Scientist and the Storyteller Workshop. Subscribe for updates on new training details and registration deadlines. Contact the Scientist and the Storyteller Workshop team. 

The Mendelian Randomization Boot Camp is a two-day intensive combination of seminars and hands-on analytical sessions to provide an overview of the concepts, techniques, packages, data sources, and data analysis methods needed to conduct Mendelian Randomization studies.  This two-day intensive boot camp integrates motivation for Mendelian randomization studies, statistical concepts, genetic considerations, and practical examples to design, implement and interpret a Mendelian randomization analysis. Led by a scientist with several award winning papers on Mendelian randomization combined with extensive expertise in epidemiology, the workshop will integrate seminar lectures with hands-on computer sessions to put concepts into practice. Emphasis will be given to leveraging existing publicly available resources (data, tools and packages) as well as indicating the scope for new studies. The afternoon lab sessions will provide an opportunity to work hands-on with real data. Participants will learn and practice all the steps required for a successful Mendelian randomization analysis using publicly available data, including identifying suitable data sources, data extraction, data alignment, assumption checking and sensitivity analysis. By the end of this Mendelian Randomization training, participants will be familiar with the following topics: Principles of Mendelian Randomization Implementation options Suitable publicly available data sources Data interpretation and handling Data analysis Sensitivity analysis Study design advantages and pitfalls Emerging Mendelian randomization techniques Use of MR-Base Audience and Requirements Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training: Each participant is required have a working laptop or tablet with video and audio capabilities. The Boot Camp will use data sets in R/RStudio using the Posit Cloud (formerly RStudio Cloud) platform, therefore it is required that each participant has previous experience using R. Each participant must have a free, basic Posit Cloud (formerly RStudio Cloud) account prior to the first day of the boot camp. Instructor Mary Schooling, PhD, CUNY School of Public Health. Additional Information Subscribe for updates on new Mendelian Randomization Boot Camp details and registration deadlines. Contact the Mendelian Randomization team. Capacity is limited. Paid registration is required to attend.

The Bayesian Modeling for Environmental Health Workshop is a two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications in Environmental Health. This two-day intensive workshop introduces the ideas of Bayesian inference and modeling in the context of Environmental Health, designed to be as approachable and friendly as possible while still providing technical and practical know-how. Led by a team of scientists with many years of diverse combined experience, the workshop will integrate seminar lectures with hands-on computer sessions to put concepts into practice. Several examples will be given using existing data, and conversations on starting new investigations with attendees' research questions will also be encouraged. The lectures and lab sessions will give an overview of the principles of Bayesian inference, as well as how to deal with different data structures, the various software options available, different types of analyses, and current and future research. By the end of the workshop, participants will be familiar with the following topics:  Principles of Bayesian inference Practicalities of Bayesian inference Software options Priors and hyperpriors Different data structures (spatial, point, continuous, categorical) Advantages and drawbacks of Bayesian approaches Temporal modeling Spatial modeling Spatiotemporal modeling Hierarchical modeling Forecasting Software options Examples of use Examples of current and future research AUDIENCE AND REQUIREMENTS Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training: Basic familiarity with R and R studio (how to download R/R studio, and how to install a package) is recommended to get the most out of the workshop.  Familiarity with spatial and temporal data structures, as well as exponential family distribution types (normal, Poisson etc.) would also be useful, though not essential. Each participant is required to bring a personal laptop as all lab sessions will be done on your personal laptop. Each participant will be using RStudio Cloud to carry out tasks while attending the Workshop. Instructions for the basics of RStudio Cloud. ADDITIONAL INFORMATION Subscribe for updates on new Training details and registration deadlines. Contact the Boot Camp team. Capacity is limited. Paid registration is required to attend.