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DEVCOM Army Research Laboratory

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Postdoctoral Fellowship in Quantum Information, Sensing and Metrology DEVCOM Army Research Laboratory in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

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Country

United States

University

DEVCOM Army Research Laboratory

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Keywords

Computer Science
Mathematics
Reinforcement Learning
Metrology
Optimal Control
Quantum Optics
Many-body Systems
Quantum Sensing
Quantum Communication
Physics
ML

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About this position

Quantum Information, Sensing and Metrology is a postdoctoral fellowship in the Computational and Information Science Directorate, Network Science Division, at the DEVCOM Army Research Laboratory. The project sits at the intersection of theoretical and computational physics, with research directions centered on quantum information science and quantum technologies.

The fellow will work on problems such as optimal control methods for quantum systems, computer-algebraic tools for modeling quantum networks, reinforcement learning for quantum network topology design, and control strategies for quantum sensing devices including atomic interferometers and quantum gyroscopes. The role is explicitly computational and theory-focused, with a strong emphasis on algorithmic development and modeling.

The position is based in the Open Campus area of the Adelphi Lab Center in Adelphi, Maryland, near the University of Maryland at College Park. The work is part of a broader research environment in SEDD, the Army’s center for research and development across the electromagnetic spectrum, and the fellowship includes collaboration with MIT, Stanford, and other leading universities.

The appointment is renewable yearly for up to three years, and the fellowship is available immediately. It is open to non-U.S. citizens and may be supported by J1 or F1/OPT visa sponsorship.

Funding details

Available

What's required

Applicants should have a PhD in physics and a background in AMO physics, many-body physics, quantum information, quantum control, or quantum optics. Programming experience in Python or a similar language is mandatory. Experience with machine learning techniques, optimal control theory, and/or open-source software development is welcome but not required. The fellowship is open to non-US citizens and can be supported by a J1 or F1/OPT visa.

How to apply

Email a cover letter and CV to Dr. Vladimir S. Malinovsky. Submit the online application in Zintellect and provide the required CV, three reference forms, and transcripts. If selected, you will also be asked to upload a research proposal through the ARL-RAP process.

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