10 computer-algorithm-"Prof"-"Washington-University-in-St" Fellowship positions in United States
Sort by
Refine Your Search
-
-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
-
postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
-
to collaborate with Prof. Robert Riener at ETH Zürich, a leader in Rehabilitation Robotics. Projects span human subjects research, computational modeling, and robotic technologies. This position is ideal
-
-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
-
postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
-
pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the
-
postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
-
-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
-
pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the
-
has also been developing physics-based machine learning algorithms for three dimensional seismic modeling, imaging and inversion using high performance computation including parallelization on GPUs