Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- Nanyang Technological University
- National University of Singapore
- Zintellect
- City of Hope
- Nature Careers
- University of British Columbia
- University of Nottingham
- Center for Biologics Evaluation and Research (CBER)
- Harvard University
- Instituto de Engenharia Mecânica
- Queen's University Belfast;
- SUNY University at Buffalo
- Simula Research Laboratory
- UCL;
- UNIVERSITY OF SOUTHAMPTON
- University at Buffalo
- University of California
- University of Idaho
- University of Stavanger
- 10 more »
- « less
-
Field
-
of large-scale genomic and transcriptomic datasets ('big data'), with hands-on experience in high-performance computing (HPC) environments (e.g., command-line interface, scripting in R/Python, use of common
-
for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components
-
Python, NCL, and MATLAB. Should have proficiency in scientific computing, high-performance computing (HPC), and scripting (e.g., Bash, CDO/NCO). Should have strong quantitative and analytical skills in
-
cloud platforms for compute and storage. Version Control & CI/CD: Git, automated testing, deployment workflows. Experience with Linux systems, HPC, and distributed computing environments. Knowledge
-
structural analyses; setup of high-performance computing (HPC) and usage of grid generators; Study of key grid generator parameters; - Automatic Component Grid Generator: Development of a grid generator script
-
. Familiarity with public health challenges related to tuberculosis Familiarity with high-performance computing (HPC). About Working at the Crick Our values Everyone who works at the Crick has a valuable role to
-
with Linux/Unix and HPC systems (SLURM) Experience with version control (Git/GitHub) Understanding of statistics for genomic analysis Preferred: Long-read sequencing analysis experience Proficiency in a
-
and selections of data) and fine-grained evaluation in the development of large language models. LTG members have access to large-scale computational resources through national and European HPC
-
quantum computing, aiming to solve small, complex sub-problems using Quantum Process Units (QPUs) while leveraging classical High-Performance Computing (HPC) on data-intensive tasks. With dedicated
-
scientific software development. Proficiency in C/C++ and Python, with experience in HPC environments (e.g., MPI/OpenMP; GPU experience a plus). Record of peer-reviewed publications appropriate to career stage