28 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" Fellowship positions at City of Hope
Sort by
Refine Your Search
-
Listed
-
Field
-
single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
-
or more statistical or scripting languages, preferably R or MATLAB. Knowledge of survival-based statistical analysis, such as Cox regression and Kaplan-Meier analysis. Working knowledge of machine learning
-
a relevant field. City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about
-
, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, pleaseCLICK HERE . Please note: City of Hope is committed to a safe and transparent
-
. To learn more about our Comprehensive Benefits, pleaseCLICK HERE . Please note: City of Hope is committed to a safe and transparent hiring experience. Please be aware that scammers may attempt to impersonate
-
or more statistical or scripting languages, preferably R or MATLAB. Knowledge of survival-based statistical analysis, such as Cox regression and Kaplan-Meier analysis. Working knowledge of machine learning
-
. Programming experience in Python, Matlab, and SQL. Mathematical modeling and data analysis. Machine/Deep learning (e.g. Pytorch, TensorFlow, JAX). City of Hope employees pay is based on the following criteria
-
productivity reflected in first author publications in peer-reviewed journals. · Willingness to apply for fellowships and training grants. · Willingness to learn and establish new methodology
-
criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, pleaseCLICK HERE . #PD
-
machine learning. The successful candidate will develop and apply methods that integrate multimodal molecular and clinical data (genomic, epigenomic, transcriptomic) across serial patient timepoints