Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
. Experience with algorithm design, embedded DSP development, multithreaded programming, GPU development, SDR hardware platforms, FPGA development, and/or Linux-based designed tools is desired. Representative
-
. First, efficient and scalable training procedure are still needed, irrespective of whether the training is done off-line on a traditional GPU-based architecture, on neuromorphic hardware. Second
-
of neuromorphic systems for different types of onboard sensing and processing tasks in the space environment. Your research will be guided by your own expert judgement and insight into current trends in AI hardware
-
numerical studies from planets to galaxies and linking them together cohesively. We expect successful applicants to work towards improving the collaborations and connections among the different areas. We
-
platforms. Assist with other software development, data analysis and visualization tasks as needed across different projects. Contribute to the development of ML and AI components within GEG software
-
Resnick Sustainability Institute at Caltech seeks a dedicated InSAR Processing Analyst to support education and research on a variety of different applications of Interferometric Synthetic Aperture Radar
-
and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
-
of the center, and we promote agile and digital skills throughout the center. Prof. Matthias Tschöp (Dr. Med., Dr. hc.), CEO of Helmholtz Munich: "We believe that excellent research requires a range of different
-
project compliance with different policies, procedures, directives, and mandates. Complies with institution, state and federal regulatory policies, procedures, directives, and mandates. Analyzes and
-
based on C/C++ and Linux) for heterogeneous distributed computer systems, assistance in running experiments, and system administration for the project’s special hardware (such as GPU servers, Raspberry-Pi