As the founding mission of UTMIST, academic events and projects have been incredibly important in supporting our undergraduate students in the academic/research careers. In the past, UTMIST has also produced educational videos in the MIST101/102 courses, and the Department is responsible for developing new content as appropriate to keep up with new research and trends.
Projects at UTMIST are self-directed experiences for students to be exposed to academic research and develop relevant skills for a career and graduate school. Directors will recruit and lead their own team of developers to work on a research project in analysis, reproduction, or exploration in machine intelligence. More advanced teams are encouraged to pursue publication in journals, conferences, or workshops. Students working on these teams will also have opportunities to network with graduate students and professors.
The Automated Machine Learning Group (AutoMLG) is an independent undergraduate research group affiliated with UTMIST that explores the growing deep learning subfield of automated machine learning (AutoML). In the past, we have conducted a study of neural architecture search (NAS) and developed techniques to evaluate the robustness of certain NAS algorithms. As part of the group, you will join us in developing ideas, implementing designs, and/or carrying out experiments towards publication.
Discord Server: https://discord.gg/dZMrQqBwzG
Academic Directors are critical members of UTMIST’s Department of Academics - the team responsible for all educational endeavors related to Machine Learning. As Academic Directors, you will develop and lead workshops in the domain of expertise, host paper readings, host beginner office hours, support the operations of UTMIST’s Mentorship Program, and work closely with the VP Academics to consolidate relevant educational ML content.
Requirements: We are looking for a strong academic record. You will have probably completed at least one course related to machine intelligence and can comprehend academic papers and articles. Candidates should have reasonable proficiency in English communications skills and have experience with organizing workshops and paper reading discussions. Relevant work experience, such as research, engineering, and/or teaching in the field of machine learning is a plus.
Instructions: Recruitment form
Application Due: Monday, September 25, 2023
We currently don’t have Research openings. Check back later!