Collaborate with YERC
Are you interested in analyzing, extending, building upon, or writing about our enormous collection of large-scale, long-term datasets in the Yellowstone ecosystem to gain a deeper understanding about the inner workings of an ecosystem? If so, then join us to translate these efforts into adaptive, informed decision-making and sustained policies to make your ecosystem a model for the rest of earth's biosphere.
NCUR 2020 hosted by MSU-Bozeman! We have several opportunities available for undergrad research projects.
Ecology Field Tech Application Engineering Build cell phone app to facilitate the collection of data by field techs and upload data to cloud-based services. Data examples include: water temperature, water quality (pH, total nitrogen, etc), macro invertebrate identification.
RiverNET Data Mining Project includes involvement with the the data acquisition and pre-processing of data from remote sensors from the Upper Yellowstone Watershed into common data formats and/or graph models. Data mining and visualization tools such as Microsoft Power BI would then used to discover/analyze and display the results.
SWAT-MODFLOW - Interdisciplinary Capstone project with Computer Science, Ecology Apply and adapt the open-source SWAT-MODFLOW predictive model using cloud-based services for use on the Mill Creek watershed. Mill Creek is tributary of the Yellowstone River in Paradise Valley. SWAT-MODFLOW is an existing open-source, integrated hydrologic model that utilizes the land surface processes of SWAT (Soil-Water-Assessment Tool), which was developed for agricultural applications.
option 1 Apply machine learning techniques to build simple identification model that can be used in camera traps. Model will be used to determine if an image contains an animal or human. If an animal, send to cloud for further identification
option 2 Use images from Yell Wild Yellowstone Visitor Challenge, apply machine learning techniques to build
Initial species identification models
Refine model to identify species specific attributes: male/female, young/old, as well as individual animals
Camera Trap/Paintball Gun – Interdisciplinary Capstone project: Computer Science, Mechanical Engineering Camera trap integrated with a paintball gun. The paintball gun firing to mark an animal is triggered by the detection of an animal image taken by the camera.
We have enormous datasets that needs to be analyzed and projects in mind that would be ideal for new graduate students, whether they are across the road at Montana State University or across the world at another academic institution. Having access to world-class datasets is also a way to get ahead of the competition for those coveted graduate student positions, and can be used to leverage funding and sponsorship by an advising professor. Take a look at our past and current work on the projects pages to see what appeals to you, then contact us to find out about data available for your project.
Current projects include:
Water Temperature Predictive Modeling Using machine learning techniques such as gradient boosting trees for regression as well as traditional statistical analysis methods, build a model to predict water temperature using input datasets such as weather data.
Deep Neural Net Research Research to determine applicability of deep learning architectures such as graph models or generative adversarial networks (GANs) for identifying previously unknown relationships within a repository of ecology datasets. These tools could also be used with existing tools such as stacked datasets that are temporally and spacially aligned to identify the data needed for a specific modeling analysis.
We have identified a unique niche of experienced, forward moving ecologists fully charged with potential on the career path towards academia, agency work, or private research in our post-masters degree program. Even if we do not have paid positions available, post-masters ecologists who can contribute their expertise in exchange for a per diem and housing can obtain both career and life changing opportunities taking a leading position on one of our current projects or proposing and running a project of their own using one of our datasets. We are always welcome to experienced, independent, career motivated individuals who can benefit our research as well as their own careers.
We also offer classic post-doc positions, yet ours focus on the transdisciplinary approach of Adaptive Ecology. Funded post docs can likewise find a wealth of opportunities to explore our data, expand their careers, and experience Yellowstone. Please contact us if Adaptive Ecology meshes with your PhD research.
Professors on sabbatical, retired or mid-career agency professionals, NGO scholars, folks with years of experience in the field—if your career has given you the skills and experiences needed to rise to the top of your field, but has yet to provide the kind of personally fulfilling experiences you have always dreamed of, come join us in Yellowstone. More than just work, your ideas, wisdom, insights, and professional connections can be a significant and greatly appreciated contribution to YERC.
Not all of our needs are in the field or are capable of being accomplished at our lab/office, but rather require an interdisciplinary community of experts who may be anywhere around the world. Computer programming, website maintenance, even artistic interpretations or contributions to help our work reach a wider audience are just some of the ways people can collaborate with YERC remotely. If you have a passion for Yellowstone and the idea of Adaptive Ecology, we can find an opportunity for you to be involved, whatever your skills are and wherever you may be.