Quantum Algorithms Intern (AI)
Мэтч & Сопровод
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Описание вакансии
TL;DR
Quantum Algorithms Intern (Quantum Computing): Researching and developing quantum algorithms for logistics, finance, and signal intelligence applications with an accent on NISQ-era quantum computers and hybrid classical-quantum systems. Focus on implementing and evaluating quantum optimization methods on simulators and physical quantum hardware.
Location: Only U.S. citizens are eligible to apply. Remote for candidates outside the Utica-Rome, NY area; hybrid/onsite for candidates within commutable distance to Rome, NY.
Salary: $20–$45 per hour
Company
is a US-based company specializing in cutting-edge research including quantum computing, AI, and cyber technology.
What you will do
- Explore the use of quantum algorithms for applications in logistics, finance, signal intelligence, and networking.
- Develop and characterize hybrid classical-quantum solutions.
- Implement and evaluate quantum optimization methods on quantum simulators and computers.
- Advance quantum algorithms through the development of novel solutions on NISQ-era hardware.
Requirements
- Pursuing a BS/BA, MS, or PhD in applied physics, computer science, mathematics, or a closely related field.
- Must be a U.S. citizen.
- Experience in classical optimization methods, machine learning, quantum optimization, or computational physics.
- Experience using quantum simulation tools such as PyTorch Quantum, Qiskit, Pennylane, or Cirq.
- Knowledge of quantum logic gates and physical qubit technologies.
- Pass a mandatory background check.
Nice to have
- Specialization in Quantum Information Science.
- Knowledge of problem-spaces where quantum algorithms are applied, such as QUBO for optimization.
Culture & Benefits
- Opportunity to work in the Utica/Rome area, a hub for cutting-edge cyber technology research.
- Collaboration with researchers and scientists on advanced government-related contracts.
- Exposure to a wide variety of technologies, including AI-enabled edge devices and machine learning.
- Flexible remote work options for non-local candidates.
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