Quantum Machine Learning Engineer Jobs (NOW HIRING)

Department
The NexCom Laboratory (Laboratory for Next-Generation Computation) at the FAMU-FSU College of Engineering invites applications for a Research Faculty I position in Quantum Scientific Computing.
Responsibilities
The successful candidate will play a key role in building a nationally recognized research program in Quantum Scientific Computing. The position offers the opportunity to conduct cutting-edge interdisciplinary research, develop externally funded research programs, build collaborations across engineering, mathematics, computer science, and quantum information science, supervise graduate students and postdoctoral researchers, and help establish the NexCom Laboratory as a leader in next-generation computational science.

• Develop novel quantum algorithms for scientific computing and engineering applications.
• Investigate opportunities for quantum advantage in computational mechanics, scientific computing, and engineering simulation.
• Develop scalable quantum algorithms for finite element methods, linear systems, eigenvalue problems, optimization, and multiscale simulation.
• Develop algorithms for both NISQ and fault-tolerant quantum computing (FTQC) architectures.
• Advance modern quantum algorithmic frameworks, including block encoding, QSVT, and quantum linear algebra.
• Develop quantum machine learning (QML) and hybrid quantum-classical methods for engineering and scientific computing.
• Implement, benchmark, and evaluate algorithms using state-of-the-art quantum software frameworks and quantum hardware platforms.
• Collaborate with researchers across engineering, computer science, mathematics, physics, and quantum information science.
• Lead and contribute to competitive research proposals to federal agencies, industry, and private foundations.
• Publish research findings in leading journals and conferences.
• Supervise graduate students, postdoctoral researchers, and research staff.

Qualifications
Ph.D. in Mechanical Engineering, Aerospace Engineering, Applied Mathematics, Computer Science, Physics, Electrical Engineering, Computational Science, or a closely related discipline.

• Demonstrated expertise in scientific computing, computational mathematics, numerical linear algebra, or computational mechanics.
• Demonstrated knowledge of quantum computing, quantum algorithms, or quantum information science.
• Strong programming skills in Python and C/C++.
• Experience with quantum software frameworks such as Qiskit, PennyLane, Cirq, Classiq, or similar platforms.
• Demonstrated record of scholarly publications in high-quality conferences and peer-reviewed journals.
• Demonstrated ability to develop innovative research ideas and work collaboratively in interdisciplinary research environments.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience developing quantum algorithms for scientific computing, computational mechanics, or engineering applications.
• Experience with quantum machine learning, variational quantum algorithms, hybrid quantum-classical algorithms, or quantum optimization.
• Background in finite element methods, computational mechanics, scientific computing, numerical linear algebra, or high-performance computing.
• Experience using cloud-based quantum computing platforms and current quantum hardware.
• Experience developing externally funded research proposals.
• Experience mentoring graduate students, postdoctoral researchers, or research staff.

Other Information
About the College of Engineering
Located in Tallahassee, Florida, the FAMU-FSU College of Engineering is the nation's only jointly operated college of engineering, combining the complementary strengths of Florida State University and Florida A&M University. The College offers an exceptionally collaborative and interdisciplinary research environment with internationally recognized expertise in artificial intelligence, computational science, quantum science and engineering, advanced manufacturing, biomedical engineering, high-performance computing, and materials research. Faculty and students benefit from close collaborations with the National High Magnetic Field Laboratory, the Center for Advanced Power Systems, regional healthcare partners, and a growing network of federal laboratories and industry collaborators.
Helpful
The NexCom Laboratory develops next-generation computational methods that integrate scientific computing, artificial intelligence, and emerging computational paradigms to solve challenging problems in engineering, medicine, and science. Our research spans computational mechanics, scientific computing, machine learning, computational modeling, computer graphics, and quantum computing, with an emphasis on developing transformative computational technologies with real-world impact.
Quantum Scientific Computing is an emerging interdisciplinary field at the intersection of quantum computing, scientific computing, applied mathematics, and computational science. Our research seeks to discover and exploit quantum advantages for computationally intensive problems arising in engineering, physics, and data science. We investigate both Noisy Intermediate-Scale Quantum (NISQ) and Fault-Tolerant Quantum Computing (FTQC) paradigms, developing algorithms that deliver practical performance gains on near-term quantum hardware while laying the theoretical foundations for scalable quantum scientific computing on future fault-tolerant quantum computers.
Current research focuses on quantum algorithms for finite element analysis, computational mechanics, scientific computing, linear systems, eigenvalue problems, reduced-order modeling, multiscale methods, quantum machine learning (QML), and quantum optimization. Emphasis is placed on modern quantum algorithmic frameworks, including block encoding, Quantum Singular Value Transformation (QSVT), quantum linear algebra, and hybrid quantum-classical algorithms. Our goal is to identify, develop, and demonstrate quantum algorithms that provide meaningful quantum advantages for engineering and scientific computing problems across both NISQ and FTQC architectures.
Contact Info
Review of applications will begin immediately and will continue until the position is filled. Questions about the position should be directed to Dr. Suvranu De, Search Committee Chair, at sde@eng.famu.fsu.edu .
University Information
One of the nation's elite research universities, Florida State University preserves, expands, and disseminates knowledge in the sciences, technology, arts, humanities, and professions, while embracing a philosophy of learning strongly rooted in the traditions of the liberal arts and critical thinking. Founded in 1851, Florida State University is the oldest continuous site of higher education in Florida. FSU is a community steeped in tradition that fosters research and encourages creativity. At FSU, there's the excitement of being part of a vibrant academic and professional community, surrounded by people whose ideas are shaping tomorrow's news!
Learn more about Florida State University and our campuses .
Anticipated Salary Range
This is a 12-month, permanent, non-tenure-track faculty appointment at Florida State University with a competitive salary and benefits package. The starting date for this position is negotiable.
FSU Total Rewards
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How To Apply
If qualified and interested in a specific Faculty job opening as advertised, apply through the FSU Faculty Careers site (jobs.fsu.edu). If you are a current FSU employee, apply through myFSU Self Service.
Applicants are required to complete the online application with all applicable information. Applications must include education details even if attaching a Vita.
Applications should include the following documents:

• A letter of interest
• Most current curriculum vitae
• A research statement
• The names and contact information of three references

Considerations
This is a Faculty position.
This position requires successful completion of a criminal history background check .
This position is open until filled.
Equal Employment Opportunity
FSU is an Equal Employment Opportunity Employer.