Sort by
Refine Your Search
-
, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
-
-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
-
functional supervision over graduate and undergraduate students. The appointment generally does not extend beyond two years. To learn more about the work in the group, checkout out the group website. https
-
. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
-
Fall 2026 opening for a Postdoctoral Research Associate to work with the recently established Simons Collaboration on the Physics of Learning (physicsoflearning.org). The Simons Collaboration is
-
-learning based exoskeleton controllers to work across tasks Designing and validating new robotic lower-limb prostheses Exploring other high-risk high-reward research areas related to device design, control
-
learning/AI, and science of science, as well as quantifying art. The BarabásiLab's current work spans the applications of networks toward understanding food and nutrition, human diseases, disease progression
-
eligible for hire as part-time lecturers for the 2027 summer terms on a per-course basis. Responsibilities Postdoctoral Teaching Associates teach 3 in-person courses per semester in First-Year Writing and
-
responsibilities, but there is an opportunity to teach if desired. The preferred starting date is September 1, 2025. Position Type Research Additional Information Northeastern University considers factors such as
-
at Northeastern University in Boston has a Fall 2026 opening for a Postdoctoral Research Associate to work with the recently established Simons Collaboration on the Physics of Learning (physicsoflearning.org