About the Program
A hands-on training opportunity to learn about the application of advanced data analysis and image processing techniques (e.g. machine learning) in musculoskeletal research and clinical care. During this program, the trainees will be assigned to a project and mentored by a team of researchers and clinicians to achieve the project goals. This training program is focused on:
- Familiarizing medical students to advanced analytical methods used to process big data and medical images
- Exposing engineering students to applications of advanced analytical methods to address unmet needs in research and clinical care of patients with musculoskeletal conditions
Program Requirements
Outside of coursework, we expect this to be your primary academic activity. As it takes time to familiarize oneself with a research project and to make significant contributions, we expect that students will be involved for at least 6 months (1 year is strongly preferred).
Minimum time commitment of 10 hours per week.
Candidate Requirements
Here are some values that we would like to see in you:
Hard Working
We expect you to have a strong work ethic. Many of us work evenings and weekends because we love our work and are passionate about our mission. We also value velocity, and like people that get things done quickly.
Flexibility
You should be willing to dive into different facets of a project. For example, besides developing algorithms, you may also need to work on data collection, manual segmentation, or manual chart review. This will also require going outside your comfort zone, and learning to do new tasks in which you're not an expert.
Learning
You should have a strong growth mindset, and want to learn continuously. We will prioritize your learning and help point you in the right direction; but you need to put in the work to take advantage of this.
Teamwork
We work together as a team. You are expected to support and collaborate with others; in turn you will also receive support from your teammates.
Participate in our Bootcamp
Please send your resume and a short (2 paragraph) cover letter explaining why you would like to get involved. We will review the applications on a rolling basis.
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