81 genetic-algorithm-computer-"UCL" Postdoctoral positions at University of Minnesota in United States
Sort by
Refine Your Search
-
. Qualifications Required Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field who possesses strong interest in genetics/biomedical applications, and strong computing
-
Previous Job Job Title Post-Doctoral Associate in AI for Genetics Next Job Apply for Job Job ID 368882 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job
-
outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and
-
Previous Job Job Title Post-Doctoral Associate - Electrical and Computer Engineering Next Job Apply for Job Job ID 369523 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular
-
Previous Job Job Title Post-Doctoral Associate - Computation (Hanany) Next Job Apply for Job Job ID 369600 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular
-
/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
-
. The incumbent will be responsible for development of gene mapping populations, pathogen inoculation and phenotyping, marker design and genetic mapping, DNA cloning, and functional characterization of candidate
-
) and developing meaningful scaled score formulas and metrics. The post-doctoral associate will support multiple aspects of this work, including conceptualization and design of the scale scores, computing
-
Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job The Blythe Lab in the Department of Genetics, Cell Biology and Development seeks a postdoctoral associate to join our team
-
techniques in cell biology, molecular biology, and mouse genetics to tackle major questions in metabolic health and disease. We are committed to fostering a supportive, inclusive, and rigorous scientific