82 algorithm-development-"Multiple" Postdoctoral research jobs at Princeton University
Sort by
Refine Your Search
-
development in Prof. Rabitz's lab, to produce the world's first nanoscale dual-frequency comb laser spectrometer. The resulting instrument will have many applications; notably, it will allow the spectroscopic
-
developing biotechnological solutions to address challenges in renewable energy, sustainable manufacturing, and human health. Our group specializes in dynamical and spatial control of engineered metabolisms
-
Tufekci in the field of social movements, especially as how it relates to changes in the public sphere with technological developments. The position will be awarded to an emerging scholar who will devote
-
of ecology, evolution, and/or behavior, while also contributing to Princeton University's excellence and diversity, broadly defined. The Program is intended to foster the onward scientific careers
-
of intracellular spatiotemporal organization, biomolecular self-assembly, and soft condensed matter. The successful candidates will develop computer simulation approaches to understand compartmentalization inside
-
University community. This mission is pursued and supports the University's purpose by using current knowledge of health and human development to guide responsive, high quality clinical, prevention, and
-
assisting with managing the lab and projects. We also expect that you will collaborate with the ARG team on developing grant proposals. Qualifications Required qualifications: Doctoral degree in a related
-
collaborate with the ARG team on developing grant proposals. Qualifications Required qualifications: Doctoral degree in a related field, such as Architecture, Civil Engineering, Robotics, etc. Excellent track
-
addition to the aforementioned project, the appointee will have opportunities to develop additional projects with members of Dr. Sinclair's lab and/or maintain their on-going work. The work location for this position is in-person
-
fields. Candidate must have excellent computational and bioinformatic skills; abilities for developing simulation models will be highly valued; experience with ancient DNA genomic datasets is encouraged