Introduction
At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world.
Your Role And Responsibilities
IBM Research is seeking a research scientist to advance novel quantum algorithms across quantum simulation and machine learning. The role focuses on developing quantum algorithms for simulating physical systems, quantum models for classical and quantum data, hybrid quantum-classical learning workflows, and theory and benchmarking of quantum vs classical learning models.
- Develop novel quantum algorithms that combine quantum and classical resources for simulation of physical systems, including ground states, thermal states, time evolution, and open-system models.
- Demonstrate quantum algorithms on real-world applications in physics, chemistry, and materials science.
- Improve upon and develop novel quantum machine learning methods that combine quantum and classical resources for learning tasks on classical and quantum data.
- Develop hybrid workflows that combine measurement data from quantum experiments with classical ML to predict properties of quantum systems.
- Develop learning theory results for QML, including generalization and complexity bounds, and identify settings showing separation between quantum and classical approaches.
- Expand the quantum ecosystem and connect to ML and quantum communities through working groups and collaborations.
Preferred Education
Doctorate Degree
Required Technical And Professional Expertise
- Experience in academic graduate program related to applicable fields (e.g., quantum computing, quantum algorithms, machine learning, computer science, statistics, information theory).
- Experience developing and/or analyzing quantum algorithms for simulation (ground states, thermal states, dynamics, or related).
- Experience with quantum machine learning and/or hybrid quantum-classical learning workflows.
- Experience implementing research code, ML frameworks, and Qiskit.
- Experience running demonstrations on quantum processors.
Preferred Technical And Professional Experience
- Strong publication record in high-impact journals or top conference proceedings.
- Programming experience in core & scientific language (e.g. python, numpy, scipy, matplotlib) and Qiskit.
- Experience with tensor-network methods for many-body systems (e.g., MPS/MPO), including DMRG, and with iterative ground-state solvers for extremal eigenpairs (e.g., Lanczos, Davidson).
- Familiarity with Git and/or Github.
- Successful record of collaborative work.
- Experience leading research projects in industry or academically.
