As a research scientist, you will develop production implementations and circuit optimizations for AI and ML algorithms on IonQ\u2019s quantum hardware. You will identify and analyze core mathematical operations and find new approaches to solving business-critical problems.<\/p>\n
A technology\u2019s efficacy has as much to do with how it\u2019s implemented as its intrinsic capabilities. Effective teams deploy diverse QIST expertise to identify broad sets of potential use cases and prioritize high impact applications.<\/p>\n
When you picture a quantum computer, you might envision a big box that looks like a laptop and has some kind of physics magic going on inside. But a real quantum computer is much, much more than a regular desktop or server, as its qubits can be 1 or 0 at the same time, allowing them to perform calculations many times faster than classical computers.<\/p>\n
Businesses are investing in quantum computing and beginning to think about how to use it to gain a competitive advantage. But while the technology is promising to drive digital investment and reshape industries, business use cases are largely experimental or hypothetical at this stage.<\/p>\n
One potential application is in accelerating the development of self-driving cars, as quantum computers could help train the AI algorithms that will drive them. But more broadly, quantum computing could speed up the process of running video and image data through complex neural networks for the purpose of training AI systems.<\/p>\n