[DMANET] Postdoc in quantum approaches to discrete optimization (Sandia Labs, USA)

Our team is seeking a highly motivated Postdoctoral Appointee that is passionate about quantum computing. Are you driven by the prospect of better understanding the power and limitations of quantum computing and crafting novel approaches for realizing quantum advantages? If you are seeking an opportunity to work under the mentorship of and in collaboration with accomplished specialists in quantum information science, check us out!


On any given day, you may be called on to:

-Design quantum or quantum-inspired classical (approximation) algorithms for discrete optimization, machine learning, simulation, and other application areas

-Perform detailed analysis on the performance of quantum and classical algorithms, with the goal of identifying quantum advantages

-Contribute in a stimulating interdisciplinary environment with computer scientists, physicists, and mathematicians to develop theoretical and practical approaches for addressing real-world problems

-Publish results in relevant journals and present at conferences


Qualifications We Require

-PhD in physics, computer science, mathematics, electrical engineering or related field and possess a bachelor's in science, technology, engineering or mathematics (STEM).

-Experience with quantum information science or theoretical computer science. We encourage theoretical computer scientists interested in quantum information science but without formal expertise in such to apply.

-Good interpersonal skills as evidenced by a history of publication of results in peer-reviewed journals and external presentations at appropriate scientific conferences

-Able to acquire and maintain a DOE security clearance


Qualifications We Desire

-Some exposure to quantum algorithm design, quantum optimization, quantum complexity theory, or broader quantum information theory

-Experience with programming language such as C/C++ or Python

-Desire to work in a collaborative environment and interested in interdisciplinary research

-Experience making and delivering effective technical presentations


About Our Team

Sandia's Quantum Algorithms for Optimization and Learning and Simulation (QOALAS) and Fundamental Algorithms for Quantum Computing (FAR-QC) are DOE-funded efforts to develop new quantum algorithms for optimization, machine learning, and quantum simulation. These projects bring together a diverse team of quantum information and computer science specialists from Argonne Lab, Berkeley Lab, Caltech, Dartmouth, Los Alamos Lab, Microsoft, Oak Ridge Lab, University of Maryland, and University of Southern California. More information is available at https://www.sandia.gov/far-qc.

More broadly, the Discrete Math and Optimization Department conducts state-of-the-art research and develops mathematics and computing in support of Sandia missions. Principal areas of focus include graph algorithms, parallel computing, combinatorial optimization, integer programming, and quantum and neuromorphic algorithms. Our team delivers creative enabling technologies and software tools. The department works on a wide variety of application areas including energy systems, scientific computing, systems software, logistics, and quantum algorithms.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status


Apply at http://sandia.gov/careers, job #673907, by December 2nd, 2020.

—
Ojas Parekh
Center for Computing Research
Sandia National Laboratories

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