124 parallel-and-distributed-computing-"Meta"-"Meta"-"Meta" positions at Forschungszentrum Jülich in Germany
Sort by
Refine Your Search
-
Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
-
willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
-
(UTC) Type of Contract To be defined Job Status Other 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
-
Your Job: Quantum computers will play a crucial role in the development and optimization of battery materials in the future. In this project, you will develop innovative quantum algorithms
-
Your Job: Your PhD project will be part of an interdisciplinary research project bridging theoretical physics and theoretical computer science. In the course of this, you will work on implementing
-
of event cameras, with the goal of achieving accuracy, efficiency, and real-time performance on robotic platforms powered by edge-computing hardware. In addition, knowledge of Model Predictive Control (MPC
-
Your Job: Join our team to manage computing time resources and projects. Your tasks include: Coordination of calls for allocation processes and computing time budgets with our European partners
-
fundamentals and hands-on experience with HPC systems; parallel/distributed programming and/or solid UNIX skills Proven experience operating Machine Learning (ML) in production. Able to design, automate, and
-
(UTC) Type of Contract To be defined Job Status Other 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
-
; parallel/distributed programming and/or solid UNIX skills Proven experience operating Machine Learning (ML) in production. Able to design, automate, and maintain end-to-end ML lifecycles, including