Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Durham University
- Umeå University
- University of Texas at El Paso
- AALTO UNIVERSITY
- Aalborg University
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Linköping University
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Queensland University of Technology
- Saarland University
- Technical University of Munich
- The University of Newcastle
- UNIVERSITY OF HELSINKI
- University of Bergen
- University of Florida
- University of South Carolina
- 8 more »
- « less
-
Field
-
machine learning, computer vision, robotics, efficient inference or embodied AI, prioritising practical, reliable systems. Durham offers strong facilities: Bede HPC (128 GPU), GPU cluster (90+ GPU), LiDAR
-
Ability to curate and integrate large scale biomedical data Experience with workflow management and HPC environments Interest in RNA biology, alternative splicing and computational method development Strong
-
), especially for reactions on surfaces Hands-on experience with high-performance computing (HPC) environments, coding/scripting (Python, Bash), and version control (Git) Strong command of written and spoken
-
, interdisciplinary working environment In-house modelling, data processing and data assimilation expertise, software, and High Performance Computation (HPC) infrastructure Excellent scientific infrastructure
-
of experimental spectroscopy or diffraction techniques such as XAS, XRD, FTIR, and XPS, of molecular modeling (MD/MC, DFT), and familiarity with basic programming (Python, MATLAB) and the use of Linux/HPC systems
-
, MATLAB) and the use of Linux/HPC systems are considered merits. Consideration will also be given to collaborative skills, drive and independence, and how the applicant, through experience and skills, is
-
mechanisms that exploit past errors, and evaluating resilience empirically on challenging benchmarks. The project team has access to the national computing infrustracture, and TU/e HPC cluster SPIKE-1 . Formal
-
. Experience with web-based scientific applications, data visualization, or large-image rendering Experience with containerization (e.g., Docker) and cloud or HPC deployment of scientific software. Engagement
-
of whole rodent brains; memory-efficient I/O, tile-based or chunked processing, multi-resolution formats such as OME-Zarr) and GPU computing on cloud or HPC environments. Experience mentoring or training
-
fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling