20 machine-learning-"https:" "https:" "https:" research jobs at University of Minnesota
Sort by
Refine Your Search
-
to classify horses into multiple risk categories (e.g., very low, low, moderate, high, and very high) and also examine a new machine learning method that could improve performance in the TBs. Work to finalize
-
surveillance and preparedness planning using multiple modeling approaches. The successful candidate will develop and implement statistical and machine-learning models, integrate multi-source ecological datasets
-
transportable. A graduate student with a physics background is needed to perform software-assisted design of system components, write and apply computer programs capable of simulating MRI pulse sequences, and to
-
orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful
-
for autonomous vehicle control and teleoperation applications. Expertise in the areas of vehicle dynamics, vehicle control, localization, computer vision, sensor fusion and estimation algorithms is desired
-
. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
-
expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our
-
transportation systems and autonomous driving. • Strong understanding of generative AI, deep learning, and multimodal machine learning, with hands-on experience. • Excellent programming skills and proficiency with
-
assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment
-
landscape constrains or enables discovery. The project draws on tools from topological data analysis (e.g., persistent homology, Euler characteristic curves, discrete curvature), machine learning (e.g