Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of DSPs, FPGAs, advanced computing (e.g., GPUs, QPUs). Excellent written and oral
-
. Programming experience in C/C++ is necessary while experience in parallel and GPU computing is most desired.PX4, Pixhawk or equivalent. Ability to work well with team members and good communication skills
-
approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
-
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
-
-of-the-art GPU and data storage cluster; direct access to a Titan Krios to the LonCEN consortium and the UK national cryo-EM facility at eBIC. By joining the Costa laboratory, you will become part of a
-
work. Work in a highly cross-functional environment together with specialists in immunology and deep learning Implement newly-released machine learning models on a GPU cluster Contribute to the design of
-
physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
-
Your profile: Preferably a doctoral degree, but MSc are also encouraged to apply Expert knowledge in one or several of the following High Performance Computing GPU computing Array Computing with JAX A
-
. Proficiency in Python and either PyTorch or JAX Experience with HPC, GPU is preferred Related Skills and Other Requirements Ability to collaborate on multidisciplinary research in a collegial environment
-
for mechanical, electrical, cooling, and infrastructure systems that underpin Cornell’s computing environment, including High-Performance Computing (HPC) and Graphics Processing Unit (GPU)‑intensive workloads