STEM Professors
Overview
Handshake is recruiting exceptional STEM professors to join our AI research community. This program brings subject-matter experts together to enhance the capabilities of Large Language Models (LLMs) across specialized scientific and technical domains. We are currently seeking faculty with expertise in Mathematics, Chemistry, Biology, Physics, and Engineering. The Handshake AI Fellowship program runs year-round, though project availability will vary by discipline.
Details
- The position is remote and asynchronous - work independently from wherever you are.
- Flexible hours and the ability to work remotely, with a commitment of approximately 10 to 20 hours per week.
- Project work includes and is not limited to developing domain-specific prompts and evaluating LLM responses.
- Dedicate time researching topics that are interesting to you, with the assistance of AI.
- Learn new skills while contributing to the changing world of AI across various disciplines.
- Placement into a project will be dependent on project availability.
Qualifications
- Current or emeritus faculty (assistant, associate, or full professors) in Mathematics, Chemistry, Biology, Physics, or Engineering.
- Able to participate in primarily asynchronous work in partnership with leading AI labs.
- Confident that your domain expertise can outmatch current AI systems in understanding and explaining key concepts in your field.
- U.S.-based faculty with valid employment authorization are eligible to apply.
This program is open to U.S.-based doctoral students, candidates, and recent graduates with valid work or training authorization (e.g., F-1/OPT, J-1, H-1B).* Participants are responsible for ensuring compliance with their visa conditions and confirming eligibility with their program or visa sponsor prior to applying.
*At this time, we are unable to accommodate candidates on STEM OPT who require an i-983. Fellows with already approved i-983s, as well as those on pre-grad OPT, CPT, J-1, or H-1B, are not impacted. This position may be subject to change in the future.