Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- ;
- Missouri University of Science and Technology
- Nanyang Technological University
- Nature Careers
- The University of Queensland
- University of Oslo
- KINGS COLLEGE LONDON
- King's College London
- Monash University
- National University of Singapore
- Queen's University Belfast
- University of Adelaide
- University of Birmingham
- University of Bristol
- University of British Columbia
- University of California
- University of New South Wales
- University of Saskatchewan
- University of Sheffield
- 9 more »
- « less
-
Field
-
outstanding contributions in computer science and high-performance computing (HPC) research. About Computing Sciences at Berkeley Lab: Whether running extreme-scale simulations on a supercomputer or applying
-
packages for data processing (e.g. Bioconductor, scikit-bio, PyPI genomics packages). HPC and/or cloud computing experience (AWS, Azure, GCP) plus practical application of AI/ML or similar computational
-
cancer genomics and functional interpretation of genetic variants Proficiency in Python, R, or other bioinformatics languages Knowledge of cloud computing, and high-performance computing (HPC) environments
-
data Ability to mentor and develop bioinformaticians at all stages of the analysis project workflow Desirable criteria Excellent computational skills applied to HPC, big data, software development and
-
. Apply and upscale models to industry-relevant scenarios, deploying simulations on high-performance computing (HPC) infrastructure and integrating outcomes into commercial workflows. Collaborate and
-
modelling, including two-phase flow in fractures, stochastic permeability analysis, and upscaling to fracture networks. Deploy large scale simulations using high-performance computing (HPC) and collaborate
-
strategic partnerships Access to high-performance computing facilities including Baskerville HPC Opportunities to shape emerging research themes and networks Support for developing independent research
-
: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
-
to develop data-driven, space-time explicit precision agronomic solutions Utilizing high-performance computing (HPC) systems for large-scale geospatial data processing, model training, and validation Designing
-
bioinformaticians at all stages of the analysis project workflow Desirable criteria Excellent computational skills applied to HPC, big data, software development and web technologies Experience in teaching