Quantum Algorithms Engineer Intern 2027

At IBM Quantum, our mission is to bring useful quantum computing to the world by advancing quantum hardware, software, and algorithms. This internship provides an opportunity to contribute to research at the intersection of quantum algorithms, quantum software, and quantum hardware. The intern will work with researchers and engineers to develop, implement, and evaluate quantum algorithms for challenging problems in areas such as chemistry, materials science, optimization, and quantum machine learning. The work will involve using Qiskit and IBM Quantum systems to design experiments, benchmark algorithms, investigate scalability, and explore techniques for improving performance on current quantum processors. This is a research-oriented internship intended for a highly motivated graduate student who is interested in translating advances in quantum computing into practical demonstrations and scientific results. The intern will have opportunities to contribute to research prototypes, technical publications, and collaborations across IBM Quantum. As a Quantum Algorithm Engineer Intern, you will contribute to research and development of quantum algorithms and their implementation on near-term quantum computers. You will work at the intersection of quantum algorithms, quantum software, and quantum hardware, with opportunities to explore applications in areas such as chemistry, materials science, optimization, and quantum machine learning. The intern will work closely with quantum researchers and engineers to investigate algorithmic approaches, implement and benchmark quantum circuits, and evaluate their performance using both classical simulation and real quantum processors. The position will provide an opportunity to contribute to research prototypes, technical demonstrations, and scientific publications. Key responsibilities include: Research and implement quantum algorithms for practical scientific and computational problems. Develop and optimize quantum circuits using Qiskit and the IBM Quantum software stack. Execute experiments on real quantum processors and analyze experimental results. Investigate techniques for improving circuit performance, including transpilation, circuit optimization, error suppression, and error mitigation. Benchmark quantum algorithms using appropriate classical baselines and simulation methods. Analyze the scalability and computational requirements of quantum algorithms and identify potential bottlenecks. Contribute to research prototypes, technical demonstrations, and software implementations. Collaborate with researchers and engineers across quantum algorithms, software, and applications. Currently pursuing a Ph.D. or Master's degree in Physics, Electrical and Computer Engineering, Mathematics, or a closely related field, with research focused on quantum computing or a closely related area. Strong understanding of fundamental concepts in quantum computing, quantum information, and quantum algorithms. Hands-on experience implementing quantum algorithms using Python and at least one quantum computing SDK, preferably Qiskit. Experience with numerical computing and scientific programming in Python, including commonly used scientific computing libraries. Ability to independently formulate technical problems, design experiments, analyze results, and communicate conclusions. Experience conducting academic or industrial research, preferably with research publications or conference contributions. Strong problem-solving and analytical skills. Ability to work collaboratively in a research and engineering environment. Experience executing quantum algorithms on real quantum processors. Familiarity with the IBM Quantum platform, Qiskit Runtime, and Qiskit workflows. Experience with quantum circuit optimization, transpilation, error suppression, or error mitigation. Knowledge of variational quantum algorithms, quantum simulation, quantum chemistry, quantum optimization, or quantum machine learning. Experience benchmarking quantum algorithms against classical methods or simulators. Familiarity with tensor-network methods, MPS simulation, stabilizer simulation, or other approaches for assessing classical simulability of quantum circuits. Experience with HPC or hybrid quantum-classical computing workflows. Familiarity with software engineering practices such as Git, testing, documentation, and reproducible research. Demonstrated ability to work across disciplinary boundaries and communicate technical concepts to researchers and engineers from different backgrounds.