Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
the AliceVision library. Activity 3: Critical Code Optimization (C++/CUDA) - Adapt the code to drastically reduce computation times (target: < 1h). - Replace proprietary dependencies (InstantNGP) with a flexible
-
commonly used on Unix systems. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP
-
Proven experience with multiple parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA (Compute Unified Device Architecture) Experience in a batch HPC environment with a
-
Sensing) Programming skills: Python, CUDA, C++ Strong motivation and commitment to research, teaching and administration The successful candidate will be expected to work effectively in a team environment
-
/C++, Fortran, and/or Python Proven experience with multiple parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA (Compute Unified Device Architecture) Experience in a
-
, tensor train methods, and/or C++/CUDA programming and a solid foundation in code development is especially welcome. LanguagesENGLISHLevelExcellent Research FieldPhysicsYears of Research Experience1 - 4
-
frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
-
processing modules, notably with the PyNX software (http://ftp.esrf.fr/pub/scisoft/PyNX/ ); Support ESRF beamlines exploiting coherent X-ray imaging techniques; Conduct an original research project exploiting
-
quantum platform software such as Qiskit or cuda-q Other Information: While principally based at Brookhaven National Laboratory, candidates should be willing to travel to carry out experiments at various
-
simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go