Summer Internship: AI And Machine Learning In Education Research, ACTNext content expired - 2018-01-13
ACT is a nonprofit organization helping people achieve educational and workplace success. Our programs are designed to boost lifelong learning in schools and workplaces around the world. Whether it's guiding students along their learning paths, enabling companies to develop their workforce, fostering parent, teacher, and counselor understanding of student progress, guiding job seekers toward career success, or informing policymakers about education and workforce issues. ACT is passionate about making a difference in all we do.
Learn more about working at ACT at act.org!Responsibilities
There is a growing need for educational assessment and learning tools that capture a broad range of learner behaviour necessary for the evaluation of skills such as problem solving, communication and collaboration. A key feature of such tools is the use of interfaces that enable rich, immersive interactions and can capture student data in a multitude of sensory modalities. This project focuses on the analysis of such multimodal data to address technical challenges in extracting valid and meaningful evidence of construct competency.
This position will work on one of many subcomponents of this project, which may include innovative approaches for automated content generation and audio/visual content analysis.
Typical work-related activities include:
- Utilizing open source software for multi-sensory data capture (e.g. OpenCV) and analysis with machine learning models (e.g. LibSVM, TensroFlow etc.).
- Developing and running different algorithms for detecting features from multiple sensory data including text, audio and video. Fusing data and features from multiple modalities. Building discriminating classifiers, generative models and running analyses. These could be computer vision, NLP, statistical and / or machine learning algorithms.
- Participating in regular update meetings with supervisor(s).
- Writing reports/papers (may involve relevant research literature review) & delivering presentations
Educational Requirements: Currently enrolled and pursuing a graduate degree in Computer Science or other Engineering Disciplines.
- Experience in machine learning for computer vision and NLP applications with emphasis on deep learning based techniques
- Experience in Python, C++ a bonus. Good overall coding skills a must.
- Ability to evaluate, learn and use new technologies and design techniques quickly.
- Strong communication and technical writing skills
- Experience with machine learning libraries such as TensorFlow, Caffe, OpenCV. Algorithms/models such as CNNs, GAN, RNNs, Bayesian Networks. Exposure to HCI.