Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Argonne
- Harvard University
- University of Luxembourg
- National Aeronautics and Space Administration (NASA)
- Oak Ridge National Laboratory
- Stanford University
- The Ohio State University
- University of Washington
- Princeton University
- CNRS
- Cornell University
- Lunds universitet
- Rutgers University
- UNIVERSITY OF HELSINKI
- University of Amsterdam (UvA)
- University of Florida
- University of Lund
- University of Minnesota
- University of North Texas at Dallas
- University of Utah
- Aarhus University
- Aarhus University (AU)
- Aston University
- Chalmers University of Technology
- DURHAM UNIVERSITY
- Delft University of Technology (TU Delft)
- Duke University
- Durham University
- East Carolina University
- FAPESP - São Paulo Research Foundation
- Ghent University
- Human Technopole
- INESC ID
- Imperial College London
- Iowa State University
- KTH Royal Institute of Technology
- KU LEUVEN
- Liverpool School of Tropical Medicine;
- MUNSTER TECHNOLOGICAL UNIVERSITY
- Max Planck Institute for Extraterrestrial Physics, Garching
- McGill University
- Michigan Technological University
- National Energy Technology Laboratory (NETL)
- Purdue University
- St Jude Children's Research Hospital
- Texas A&M University
- The University of Arizona
- University of Arkansas
- University of Canterbury
- University of Colorado
- University of Miami
- University of Oxford
- University of South Carolina
- University of Southern Denmark (SDU)
- University of Texas at Arlington
- Utrecht University
- Wageningen University & Research
- 48 more »
- « less
-
Field
-
4 Jul 2026 Job Information Organisation/Company KU LEUVEN Research Field Computer science » 3 D modelling Researcher Profile Recognised Researcher (R2) Application Deadline 17 Jul 2026 - 23:59 (UTC
-
National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 18 hours ago
the early 2000s. Program Goals The Professional Internship Program is designed to introduce undergraduate students and recent Bachelor's graduates to the challenges of conducting energy research, and enable
-
to federal research proposals, sponsored research applications, and collaborative project reports. Familiarity with scalable computing environments, cloud platforms, high-performance computing, distributed AI
-
. * Proficiency in R and/or Python for data analysis and visualization. * Experience working with large datasets in an HPC or cloud computing environment. * Demonstrated ability to work independently and
-
machine learning frameworks (e.g., TensorFlow, PyTorch). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications: Experience with multi-GPU model training and
-
domains such as telecom, defence and cloud. You will join the Machine-Intelligence for Networks and Distributed Systems (MINDS) research group at the Department of Computing and Learning Systems, School
-
: Programming proficiency in at least R or Python (ideally both), plus comfortable use of Unix/Linux shell. Hands-on experience with high-performance computing (Slurm/PBS or equivalent) and/or cloud computing
-
role of land–atmosphere interactions in S2S predictability; impacts on boundary layer processes, aerosol-cloud interactions, precipitation, and hydrological extremes, including feedback mechanisms
-
RXN). Familiarity with reaction condition prediction and reaction yield optimization. Exposure to quantum chemistry (DFT) and molecular simulations is a plus. Experience with cloud computing and/or high
-
Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description