Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
/Software Engineer (Computer Systems Engineer 3/4) at the National Energy Research Scientific Computing Center (NERSC) to help architect, deploy, configure, and operate large scale, leading-edge high-performance
-
. The Department has grown substantially in the past 15 years, from 40 to 120 faculty in parallel with the remarkable growth of our hospital based affiliates as well as the city and county of Denver. Our work is
-
of programming, learning theory, parallel algorithms or quantum computing Research publications in theoretical computer science conferences and journals Experience in teaching Computer Science topics
-
Staff - Non Union Job Category M&P - AAPS Job Profile AAPS Salaried - Statistical Analysis, Level B Job Title Computational Biologist Department Kobor Laboratory | Centre for Molecular Medicine and
-
About the division/school: The Mastercard Foundation Climate Resilience and Sustainability Program is a flagship partnership between the University of Cambridge and the Mastercard Foundation
-
to develop advanced algorithms, parallel computing capabilities, and software engineering of Green’s function based multiple-scattering code for computing the electronic structure and energetics
-
, and digital forensics Programming languages and distributed and parallel computing Data science and machine learning EEO Statement: Hofstra University is an equal opportunity employer and is committed
-
- into a GPU-enabled and parallel code to run efficiently on state-of-the-art exascale hardware Designing implementations and reviewing community contributions of library features and new statistical
-
or field including associated analysis possibly involving statistical or data analytical software. Work across teams and projects, often on a number of parallel and competing tasks. Work with discretion
-
this, these simulations need to be massively parallelized. The objective of this thesis is to implement and evaluate different contingency parallelization approaches using our group's computational infrastructure