Applied Sciences Trainee

🎓 Internship

Trainee program of applied sciences group. This program provides non-experts hands on experiences on applied sciences topics with engineers / researchers / faculty members.

LocationsBerkeley, CA (Hybrid) • RemoteGroupsApplied SciencesProgramsTraineeCreate Time2026-05-04
🧾 Apply Now

Trainee

Start DateJune 15th or Rolling BasedEnd DateAugust 15th or Rolling BasedAttending TracksApplied Sciences Trainee • Computation (Quantum) Trainee • Computation (Machine Learning) TraineeLocation & ModeFull-time • Part-time • Hybrid • Shenzhen, China • Nanjing, China (Hybrid) • Aliso Viejo, CA • Saint Louis, MO • Remote • Berkeley, CA • On-siteGroupApplied Sciences • Computation

In-depth 8 / 12 weeks supervised independent or small group study with engineers, researchers, or faculty members. This program gives students opportunities to learn and work on real research problems and possibilities to continue to work with us as engineer / research intern level positions. This program is designed for students who have foundational preparation or strong interest in a specific direction, but are not yet experienced enough for advanced research or engineering topics.

Information

This is the trainee version of applied sciences engineer (Chem/Biochem/System). Topic tracks available by May 6th with Applied Science Engineer: - Quantum Physics for chemistry and biology - Polymer - Biochemistry - Deep learning application to physical system evolution - Bio/chem/physical system Dynamic modeling (with computation Engineer) Advanced Track - Quantum Biology Both formats follow the rules: If you need staff members to prepare lecture sessions for you, the mentorship fee reflects the contracted time and efforts of our mentors. For any research / project outputs, authorship will be determined based on actual contribution following standard academic practices. Intellectual property (IP) and any potential revenue distribution, if applicable, will be handled according to project-specific agreements and applicable regulations.

Alignments

Background • Chemistry, Biochemistry, Biophysics, Molecular Biology, Machine Learning or related disciplines • Exposure to physical system evolution or physical chemistry, molecular interactions, or complex biological systems Experience • Experience working with experimental systems or scientific data • Ability to read and extract key mechanisms from scientific literature • Experience thinking about systems beyond standard toolchains (e.g., not limited to DFT/MD workflows) • Exposure to interdisciplinary collaboration (e.g., with physics, computation, or modeling teams)