Prospective Students

Contents:

  1. Upcoming on-ramp events: Open houses and AI Summer Research

  2. How to join tips for each type of student (Undergrad/MS/PhD)

  3. Qualifications for joining the lab

Upcoming on-ramp events: Open houses in early Fall & Spring and AI Summer Research

The UNT Biomedical AI lab group has open house events the week before classes start each Fall and Spring on the schedule below. Come chat with the research students if you're curious about the lab, particularly if you're interested in joining a research project - but also if you just want to chat. The lab is actively recruiting students to lead or contribute to ongoing projects.

  • Aug 20, 2021 (Thursday Friday before class starts) at 4:00pm-5:15pm, location zoom at https://unt.zoom.us/j/91198508859

  • January 6, 2022 (Thursday before class starts) at 4:00pm-5:00pm, location TBD

Additionally, there are two times in the summer to hear about lab projects as part of the AI summer program. The Biomedical AI lab always has projects seeking students presented in this program, and is your best route to engage as an undergrad or MS student.

  • May 31, 2021 at 10:00am: The start of the AI Summer Research Program. Walk-ins welcome to observe. Contact Dr. Albert for event details in May.

  • June 25, 2021 at 10:00am: Presentations of progress after the 4-week intense period

Lab application form:

If you attend one of these events, and are interested in joining this lab or other labs afterwards, the following form will be open for a limited time after each event. Any responses to entries on this form with be within one week after the event. If you need a more timely response, send an email to Dr. Albert directly.

Lab application/interest form for special events

How to join - tips for each type of student

UNDERGRADUATE & TAMS STUDENTS:

Undergraduate students can gain significant, practical experience in pursuing research projects. On a regular basis we are seeking undergraduate students to assist in projects led by graduate students int he lab, with varying degrees of independence depending on skills and commitment. Note, however, that for undergraduates we generally only accept new students in the first week of regular semester classes after attending one our open house events with times listed below. We may also take new students who participate in the UNT AI Summer Research Program to continue their project as part of the lab.

MS STUDENTS:

Generally, MS students in the lab start by assisting on a project, although incoming MS students with AI/ML/Data science experience can discuss leading their own project if they have more than 1 year left in their program - note the requirements below to join. RA funding is typically not available to MS students, and priority goes to students who are already engaged in projects or students who need little training. Generally, we only take MS students during the first week of the semester, after our open house events, but there are occasional exceptions.

PHD STUDENTS:

PhD students are always welcome, though financial support is limited. Research funding for students who have not yet arrived at UNT is generally not possible. You are encouraged to apply early to UNT for TA support. RA support may be possible as well depending on grant availability, but it is important to mention this lab in your application to be sure we are aware of your desire to join the lab during the admissions process.

Requirements for joining the Biomedical AI Lab at UNT

  • Commitment: 10-15 hours per week (on average) for at least 1.5 years.

    • Why? We do not accept students in their last year, since it takes so long to train someone and the pace of research requires at least 10 hours / week absolute minimum.

  • Skills:

    • Programming: 2 years of programming courses or 3 years job experience - this is an absolute minimum, no exceptions.

      • Python is main language of the lab, but Java is often used for app development.

    • Stats/Machine Learning: At least one course of machine learning, data mining, or predictive modeling in statistics. Exceptions can be made if the course was an applied course such as NLP or computer vision.

  • Expected stats:

    • GPA > 3.3

    • TOEFL > 100 - Writing and speaking ability is critical