DRI Research Immersion Internship 2023
DRI Research Immersion Internship 2023
Internships driven by career discovery in science, technology, and entrepreneurship
Careers in science involve exploration, discovery, and continually learning new skills. This internship program is designed for students at Nevada’s state and community colleges to take the first step in their career in science.
About the Program
Science at the Desert Research Institute offers real-world, immersive opportunities to contribute to solving the STEM problems of the future.
As you consider the direction of your career, internships are a great way to discover your strengths, interests, and get paid to learn new skills to bring to your future career.
What it Involves
The DRI Research Immersion Internship program will take place during fall semester 2023. This paid internship involves working with a team dedicated to real-world problem solving with real-world scientists. Interns must be ready to take on new challenges by learning new skills and broadening their knowledge base.
After a guided training period, interns will work closely with mentors and their team members on science, technology, and entrepreneurship-focused projects that will launch both their curiosity and their careers. Students do not have to be enrolled in a science major to apply for the program, however they must be interested in learning about complex science topics.
This program is driven by inclusive excellence, and the target audience for this program is first and second-year students in Nevada’s community and state colleges.
- You are curious about science, technology, engineering, or math.
- You want to take on new challenges, expand your current knowledge horizons, and work hard.
- You are dedicated to real-world problem solving with real-world scientists.
- Four project teams are accepting applications from students who have already completed high school who are currently enrolled at CSN, GBC, NSC, TMCC, and WNC.
- One project team is accepting applications to students in dual enrollment (high school with early college credits).
- All majors are welcome.
- To apply, you need to have at least two half days (4 hr blocks) or a full day (an 8 hr block) available for the internship, between Monday and Friday during fall semester 2023. Some projects require specific schedules to apply.
This is an 8-hour per week commitment for the fall semester, up to 120 hours total. The weekly schedule will be determined by the internship mentors once students are selected.
Students earn $13/hour for their participation in the internship. The limit of hours students can work is 120.
Applications are due Wednesday May 10, 2023.
For Current College Students
Opportunities for students enrolled at CSN, GBC, NSC, TMCC, or WNC (who have completed high school).
How do Mountains Affect 100-Year Rainfall?
Mentor name: Guo Yu, PhD
Apply if you are interested in: Hydrology, data management, data analysis, statistics, R programming
About the project: Rare and extreme rainstorms and floods are the main causes of billion-dollar weather disasters across the United States. Proper management of such events requires prediction of their severity, likelihood, and impact. Rainfall frequency analysis is a statistical procedure through which we estimate recurrence intervals of rare events, such as the 100-year or 1,000-year rainfall. This project involves data analysis, followed by interpreting and presenting the results, to better understand the role of mountains in driving rainfall frequencies. Students will gain experience with data “wrangling”, basic R programming, and how to conduct linear regressions in R.
Location: Las Vegas
Requirements: A personal computer with internet capability and hard drive storage space to download additional programs.
Sowing Botanical Literacy in Early College Students Using Native Nevada Plants
Mentor name: Andres Andrade, PhD
Apply if you are interested in: Native plants, plant identification, botany, sagebrush steppe ecosystems
About the project: Scientific plant identification is a vital skill for cataloguing and conserving global plant diversity and is often a prerequisite for careers in botany, agriculture, ecology, and environmental science. This internship involves applying plant identification skills to crowdsourced photographs that have been submitted to iNaturalist. To do this, students will need to learn about plant organs (e.g., leaves), their component structures (e.g., leaf blade, petiole, and stipule), and the often-bewildering array of terms used to describe them (e.g., cordate, renoform, sagitate, etc.). Students will use a dissection microscope to examine plant organs and structures, develop a simple dichotomous key, and apply the key to identify and label publicly-submitted photographs of plant species on iNaturalist with the correct scientific identification.
Format: In-person, with availability for in-person meetings on Tuesdays, Wednesday, or Thursdays during business hours in fall 2023.
Requirements: A personal computer with internet capability and a smartphone.
The Influence of Shrub Encroachment on Ecosystem Functions of a Montane Meadow
Mentor name: Amy Langston, PhD
Apply if you are interested in: Mountain meadow ecosystems, spatial analysis, data analysis, fieldwork techniques
About the project: Montane meadows are highly valuable ecosystems that provide critical functions in Lake Tahoe watersheds. This project will investigate the potential effects of shrub encroachment on ecosystem functions at Spooner Meadow. The internship will incorporate field work, spatial analysis, and data analysis to contribute crucial data that will inform future restoration plans at Spooner Meadow. Fieldwork wil help characterize current shrub cover at Spooner Meadow and identify patterns and rates of shrub encroachment over time. On the computer, students will be responsible for managing datasets and visualizing results. Specifically, students will apply math to ecology to evaluate the relationship between shrub encroachment and local climate trends, determine the current status of ecosystem functions at Spooner Meadow, and use data analysis to infer future trajectories of shrub cover and ecosystem health at this site.
Format: In-person (outdoor fieldwork required)
Requirements: A personal computer with Microsoft Excel.
Wildfire Impacts on Mountain Watersheds
Mentor name: Gabrielle Boisramé, PhD
Apply if you are interested in: Data management, creating systems to organize information, Microsoft Excel, analyzing environmental data to test a hypothesis
About the project: To be able to understand the impact that wildfires have on mountain watersheds, soil moisture data is needed – but it is very sparse in remote regions. This project will fill some of this data gap using a set of time lapse cameras and soil moisture sensors that have been placed at multiple locations within Yosemite National Park. Before these camera images and sensor measurements can be used by researchers, they must be processed and organized into a usable format. The goal for this internship will be to turn a large collection of photos and numbers into a usable dataset of information about snowpack, soil moisture, temperature, and humidity at each study site. Creating this dataset requires is attention to detail, the ability to follow directions, and teamwork. Interns will gain experience organizing large datasets, processing information in Microsoft Excel, and working as a collaborative team. The most difficult technical challenge of this internship will be keeping the large amount of data organized.
Requirements: A personal computer with internet capability and software on their computer for viewing AVI files (such as Windows Media Player) and JPG files.
For TMCC High School Students
Opportunity for students in TMCC High school dual-enrollment program.
Using a Model and Satellite Observations to Understand Wildfire Smoke Plumes
Mentor name: Azimeh Harofteh, PhD
Apply if you are interested in: Remote sensing, modeling, data analysis, understanding implications of patterns in data
About the project: One of the biggest health impacts to humans due to wildfires is exposure to the harmful smoke and resulting pollutants. To protect against this risk and minimize exposure to the harmful pollutants, the most effective wildfire management strategy is to detect and predict the spread of wildfire smoke plumes early. This requires complex modeling and using technological tools that bring together different types of data. This project will apply remote sensing observational data from multiple satellites to a recent megafire at the western US and detect the generated smoke plumes. Interns will then use data analysis to simulate the smoke transport and track the movement of the smoke plumes. Students will work with a trajectory model called HYSPLIT, which simulates the movement and fate of air pollutants and other atmospheric particles. A high comfort level with math and an interest in data analysis are required for this project.
Requirements: A personal computer with internet browser connection and Microsoft Excel.