Hey! Are you a bug nerd? What about a debugging nerd? At the Bahlai lab, we want all kinds. We’re looking for undergraduate assistants to help us count insects, to manage home-built hardware for monitoring insects and for data and database management tasks. Position details:

Undergraduate research positions in the Bahlai Lab: Computational Ecology

Hey! Are you a techy, buggy undergraduate student interested in research experience? The Bahlai Lab at Kent State University has a mission to understand how population processes unfold over time using technology and data-driven methods. Starting in Spring 2021, we need insect and/or data and/or hardware enthusiasts to help out in PAID positions supporting graduate student research. We’re looking for motivated, enthusiastic students with strong interests in the intersection of biodiversity research, technology, and data science, people who work well in a diverse, friendly environment, and will work with us to uphold our core goal of inclusivity and equity in the sciences. Field sites are located in the Cuyahoga Valley National Park and Cleveland area.

Please contact Bahlai Lab manager Julia Perrone at jperrone@kent.edu with a CV/resume and statement of interest to apply. Applications will be reviewed on an ongoing basis but for best consideration, please apply by March 31, 2021.

Current active projects requiring assistance include:

Elevating Biodiversity: understanding how anthropogenic filters affect insect systems

  • How do the physical environments  humans build shape the communities of organisms that use them? This project examines how insect communities in green roofs and similar natural systems assemble. Elevating biodiversity? Green roofs take it up a whole level! 

Advanced insect surveillance: instrumentation for remote sensing of ground-level biodiversity trends.

  • Can we monitor biodiversity better? Insect trapping is sometimes the pits: pitfall traps, that is! Most classical methods of insect biomonitoring are messy,  time consuming, heavily dependent on highly trained experts for identification, and ultimately result in a large number of dead insects to collect data. Remote monitoring technology alongside machine learning enabled automated image processing has potential to lower lethality, time, and expertise barriers that goes alongside classical insect collection. But what are the tradeoffs?

Debugging data trends: methods for validating and humanizing big environmental data

  • How does the source of our information affect our conclusions about systems? Our understanding of ecological processes is shaped by the information we have access to about them. Mining data from citizen science surveys, government documents and other large-scale sources helps us to understand how the environment shapes information (and how information shapes the environment). We have two major projects in this area: developing text-mining approaches to look at human-landscape feedbacks in environmental regulations, and layering data sources to create ‘meta-models’ to examine how human factors affect predictions of changing species distributions.

We are looking for students with a wide array of skills to help support these projects. Tasks for students may be field, lab or remote based. Field workers must:

  • Be comfortable working outside and carrying up to 30lbs equipment through uneven terrain
  • Not be icked out by handling insect samples
  • Be able to climb ladders to access green roofs

Preferred skills: 

  • Experience with insect identification 
  • Python or R coding experience
  • Open hardware, instrumentation and programming aptitude

Because of COVID distancing restrictions, applicants will need a valid driver’s license and access to a vehicle for separate travel to local field sites. Mileage will be reimbursed. The Bahlai lab is committed to adhering to all CDC recommendations and Flashes Safe 8 regulations, and thus masking, distancing and sanitation will be required for all in-person interactions.
For more information on research in the Bahlai Lab please go to: https://bahlailab.org

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