43 parallel-programming-"Computer-Vision-Center" Postdoctoral positions at Michigan State University
Sort by
Refine Your Search
-
SWAT and MODFLOW. Exceptional Fortran programming expertise is essential and will be a major selection criterion. The selected candidate must be able to read, understand, modify, extend, compile, debug
-
candidate will conduct model verification, sensitivity analysis, calibration, validation, performance evaluation, and troubleshooting. The position requires strong scientific programming and software
-
parallel projects will ensure the development of independent projects to support the long-term career goals of the applicant. Generally, the project will center around leveraging bacterial and mammalian
-
with the Quello Center for Media and Information Policy in the Department of Media and Information and the Future of Work Initiative in the College of Social Sciences at Michigan State University. The
-
, disability or protected veteran status. Required Degree Doctorate -Chemistry, Computer Science or related field Minimum Requirements Ph.D. in Chemistry, Computer Science or related field. Computer
-
Computer programming skills Desired Qualifications Experience developing computational tools for biomolecular systems Experience training machine learning models Experience working in a collaborative
-
. Proficiency in computer programming and data analysis. Demonstrated productivity in previous work. Desired Qualifications A background in cognitive neuroscience of relevant research domains. Familiarity
-
structured representations of 3D anatomy; integrating these representations with AI reasoning models; evaluating performance on radiation therapy planning tasks against text-only and vision-only baselines
-
structured representations of 3D anatomy; integrating these representations with AI reasoning models; evaluating performance on radiation therapy planning tasks against text-only and vision-only baselines
-
. The selected candidate will work with Dr. Yuzhen Lu to develop and test automated field-deployed sensing/harvesting systems that may integrate machine vision, artificial intelligence, and mechanisms for