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.
Required education
Doctorate Degree
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.
OTHER RELEVANT JOB DETAILSIBM offers a competitive and comprehensive benefits program. Eligible employees may have access to:
- Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being
- Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs
- Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law
- Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals
- Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences
We consider qualified applicants with criminal histories, consistent with applicable law.
This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role.
The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year.
