For these positions, please apply at https://forms.gle/5dyE1hpKgcvXe1Ne6 and specify the position you are interested in. Our next round of applications will be processed starting Winter Quarter.
Apply to the Summer REU at http://e4e.ucsd.edu/apply.
E4E is looking for students who are interested in combining computer vision, game/graphics development, and archaeology to produce a ground-breaking tool to help people visualize and experience remote ruins. The full project description is here. These students will be contributing to a major project with a long history of expeditions and data.
- Computer Vision
- Machine Learning
- Game Development (Unreal Engine)
- 3D Modeling for Graphics Development
- Virtual Reality/Augmented Reality
Smartfin brings surfers and scientists together to collect important oceanic data from coastlines by developing a surfboard fin that can passively collect information and seamlessly upload it to a cloud for use by scientists. We are looking for students interested in data visualization/analysis.
- Data Visualization (Python Numpy/Matplotlib/Pandas)
The Uaso Ngiro Baboon Project looks to understand the social relations and dynamics of the baboon troops located in the plains of the Laikipia Plateau in Kenya. We are currently looking for students with experience with particle filters and computer vision to help us track the movement of baboons in aerial video.
- PyTorch/Neural Networks
On the Acoustic Species Identification team we aim to aid our San Diego Zoo collaborators in breaking into the passive acoustic monitoring field. As a preliminary deployment, our collaborators collected over four terabytes of audio recordings from the Madre de Dios region of the Peruvian Amazon. We are working to combine the powers of fields such as machine learning, digital signal processing, computer science, biology, and ecology to parse through and extract statistically significant indicators of ecological health from the world’s natural soundscapes that are begging to be heard.
- DSP for Data Manipulation
- Software Test/Documentation
- Machine Learning
Technical Contributor (Aye-Aye Sleep Monitoring)
The Aye-Aye Sleep Monitoring project is part of a remote sensor network project to develop a series of sensors that can be used to monitor animal behavior. This quarter, we are focusing on rapidly deploying a set of cameras, microphones, and vibration sensors to monitor the Aye-Ayes currently living at the San Diego Zoo in Balboa Park. We are looking for students who can contribute to the data management and analysis portion of this project.
- Familiar with multithreading/multiprocessing programming
- Familiar with networking concepts
- Familiar with test/analysis and documentation of software systems
- Web App Development
- Computer Vision/Image Processing
- Digital Signal Processing
The Burrowing Owl Action Recognition team is working to develop a comprehensive machine learning tool to recognize burrowing owls in their native habitats. This tool will assist scientists in understanding the burrowing owls’ behavior in and around their nests. We are currently looking for students to help develop the machine learning models.
- Deep Learning/Computer Vision
- ML model development
- CUDA/OpenCL experience a plus
The Radio Telemetry Tracking project seeks to build an efficient and user-friendly drone-based system of tracking animals with radio telemetry. For the upcoming quarter, we are focusing on developing this project’s software components, and we are currently seeking someone to contribute to this project’s system manager.
- Software Documentation
- Software Test/Analysis
The Mangrove Monitoring ML team develops state of the art algorithms for classifying mangrove imagery using high-resolution drone and satellite imagery. We are looking for experienced students to help in the further improvement of our current algorithms and for the development of new algorithms with a focus on publications.
- Computer Vision/Deep Learning Knowledge
- Data Science Fundamentals
- Experience with Tensorflow/Pytorch
- Experience with CNN/Unet Architectures
- Experience with Data Analysis Libraries (Pandas, Numpy, etc)
- Experience with GIS/Remote Sensing workflows
The Mangrove Monitoring Image Classification Tool team develops a tool that lets conservation scientists access and use our ML algorithms without prior knowledge to classify mangrove imagery using a web-based tool. We are looking for a student to help contribute to the testing and development of our current Image Classification Tool with additional features and performance updates.
- Web Development (HTML/JS)
- Cloud Computing (Azure/AWS)
- Experience with Azure
- Experience using ML models
Research Contributor (NSF REU)
We are now taking applications for our 2021 summer REU! If you are interested in spending the summer in San Diego working on impactful engineering projects and exciting fieldwork, please apply to be considered for our summer REU program. Go to e4e.ucsd.edu/apply to submit your application.
Last year, 18 students from universities across the US worked on projects including drone based ecological classification, 3D mapping for archaeological sites, and wildlife radio telemetry tracking. They worked with ecologists from the Scripps Institution of Oceanography and San Diego Zoo Institute for Conservation Research. Even though we were remote, all of these students were able to contribute and get a lot of experience out of all of these projects. We hope to be able to continue to provide these opportunities this coming year.
See http://e4e.ucsd.edu/news-and-updates/e4e-summer-2021-reu for more information. Apply at http://e4e.ucsd.edu/apply.