Sort by
Refine Your Search
-
• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc
-
on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
-
Institute (https://cse.umn.edu/aiclimate). The role involves building knowledge-guided machine learning (KGML) models for sustainable agricultural practices, developing AI-ready benchmark datasets, and
-
, implement, and evaluate computational models that assimilate 2-photon data (60%) Use a computer programming language to create novel neural network simulations (models) that include realistic simulations
-
the results (e.g. worksheet, graphs, tables, etc.) and assists in developing appropriate computer programs. o Analysis of data obtained as a result of experiments performed, and preparation of laboratory
-
collection and in communicating with individuals and groups in a computer networked environment. About the Department The Department of Dermatology is committed to providing excellent patient care, conducting