Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Have excellent analytics skills: statistics, optimization, stochastic modeling, etc Have excellent verbal and written communication skills Have experience in working on real A/B testing is a plus We
-
Max Planck Institute of Molecular Cell Biology and Genetics | Dresden, Sachsen | Germany | about 2 hours ago
Dynamics * Information Theory and Network Analysis * Mathematical Biology * Mathematical Machine Learning / Theory of Deep Learning * Mathematical and Theoretical Physics * Stochastic Topology Your
-
Environmental Engineering (CEE). For more information, please visit: https://earthobservatory.sg , https://ntu.edu.sg/ase , and https://ntu.edu.sg/cee . We are looking to fill a total of 5 Research
-
algorithms) High-dimensional statistics, structured/functional data Simulation, stochastic approximation/optimization Incremental, sequential, active, and reinforcement statistical learning Why join
-
should be interested in research and teaching in areas such as AI in Business Analytics, Generative AI and Business Decision-Making, Optimization, Predictive Analytics, Stochastic Processes, Data
-
a plus: research/course focus on stochastic analysis, algebra or rough paths. Knowledge of Lie theory or Hopf algebra will be considered as a benefit. Area4 - Algebra, Geometry and Topology for
-
stochasticity. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7010-JERBEC-002/Default.aspx Requirements Research Field Physics Education Level PhD or equivalent Research Field Chemistry
-
interest in, one or more of the following areas is valued: nonlinear dynamics, condensed-matter physics, and stochastic processes. The ideal candidate is an experimentalist who enjoys not only setting up
-
framework of the State Plan for Scientific, Technical and Innovation Research 2021-2023. Integration in a working team within the research group of the UPM in “Computational Statistics and Stochastic Modeling
-
University of Toronto | Downtown Toronto (University of Toronto / Harbord), Ontario | Canada | about 2 months ago
: training error, test error and cross-validation; classification, regression, and logistic regression; principal components analysis; stochastic gradient descent; decision trees and random forests; k-means