Events

This clinic is intended for STEM graduate students and postdocs who are CURRENTLY on the job market or planning to be in the fall. Get feedback on your interview skills, and prepare for online and screening interviews. Sign up for a time slot for 25 minute individual advising session. There are slots for 25 people. YOU MUST sign up ahead of time to participate; deadline to register is March 1, 2023. The event runs from March 4th to March 8th. 

Advance your career as an effective, inclusive leader in STEM through this four-part series brought to you by the New York Academy of Sciences with special guest speakers from Pfizer senior leadership. Effective leadership is a key skill for all STEM professionals, but it is often difficult to define and practice. It requires developing and honing a range of personalized skills beyond the technical knowledge acquired from pursuing a degree or working in a lab or school. Aligning these skills with an individual’s values and strengths empowers them to be a positive change agent in the world, uplifting people within and outside a single organization. This four-part series of bite-sized learning webinars are designed to build key skills as a change maker. Participants will have the opportunity to attend the webinars live or on demand. Registration required.

This interactive workshop series is your complete introduction to programming in R for people with little or no previous programming experience. It covers the basics of using RStudio, creating variables, working with data frames, and starting to analyse your data using summary statistics and data visualization. After completing this workshop series you will be able to: Navigate R Studio Open data in R and work with it in data frames using tidyverse Distinguish between different variable types Visualize data using ggplot Inspect documentation to deal with error messages R Fundamentals has 4 parts. Each of the parts takes 2 hours, and is delivered in a lecture-style coding walk through interrupted by challenge problems and a break. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. The workshop series is structured as follows: Part 1: Introduction to R and RStudio Part 2: Data frames and variable types Part 3: Manipulating data frames Part 4: Data visualizations and custom functions

Geospatial data are an important component of data visualization and analysis in the social sciences, humanities, and elsewhere. The Python programming language is a great platform for exploring these data and integrating them into your research. Python Geospatial Fundamentals: Part 1 This workshop is the first one of the two-part series on using Python for fundamental geospatial analysis and visualization. After this workshop, you will be able to: Recognize different forms of geospatial data and coordinate reference system (CRS), Use GeoPandas and matplotlib libraries to map and analyze spatial data. Python Geospatial Fundamentals: Part 2 This workshop is the second one of the two-part series on using Python for fundamental geospatial analysis and visualization. After this workshop, you will be able to: Apply more advanced Python libraries for interactive visualization. Choose domain-specific spatial datasets to create your own maps. Knowledge Requirements You'll probably get the most out of this workshop if you have a basic foundation in Python and Pandas, similar to what you would have from taking the D-Lab Python Fundamentals workshop series. Here are a couple of suggestions for materials to check out prior to the workshop. D-Lab Workshops: Python Fundamentals Python Data Wrangling and Manipulation with Pandas

This workshop provides an introduction to visualization with Python. We will cover visualization principles and plotting with Matplotlib and Seaborn, working through examples in a Jupyter notebook and documentation of each plotting package. We’ll also learn about styles and customizing plots. Throughout the workshop, we’ll discuss the plot types best suited for particular kinds of data. The following plot types will be covered: Histogram Barplot Boxplot Scatterplot Lineplot Subplot We'll also learn about styles and customizing plots. Throughout the workshop, we'll discuss the plot types best suited for particular kinds of data.