{"id":3589864,"url":"https://alion.io/job/oak-ridge-national-laboratory-postdoctoral-research-associate-ai-for-quantum-computing","title":"Postdoctoral Research Associate - AI for Quantum Computing","company":{"id":8721,"name":"Oak Ridge National Laboratory","domain":"ornl.gov","url":"https://alion.io/company/oak-ridge-national-laboratory","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"Science & Research","role_family":"Science & Research","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Monte Carlo, Monaco"],"countries":["MC"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":37000,"max_usd":83000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1296},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CUDA","optional":false},{"name":"HPC","optional":false},{"name":"Machine Learning","optional":false},{"name":"PennyLane","optional":false},{"name":"Qiskit","optional":false},{"name":"Stim","optional":false},{"name":"IonQ","optional":true},{"name":"IQM","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-30T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-30T00:00:00Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"Requisition Id17379\n­­\n\nOverview:\n\nAs a postdoctoral researcher, you will help solve some of the most challenging problems the world faces. You will perform impactful research on a range of significant problems, and you will apply your work in multidisciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and hardware-software co-design skills to bear as you develop new methods to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, and disseminate innovative results through publications and presentations.\nThe Learning Systems Group at Oak Ridge National Laboratory (ORNL) seeks a highly motivated Postdoctoral Research Associate with strong expertise in AI for quantum computing to lead research at the frontier of advanced machine learning and quantum information science. The successful candidate will leverage deep neural architectures, neural decoders for quantum error correction (QEC), error mitigation, and noise characterization to design and evaluate novel AI-assisted quantum workflows, agentic systems, and physics-informed ML algorithms for quantum computation.\nThe candidate will collaborate closely with machine learning researchers, software engineers, and quantum information scientists across the Quantum Science Center (QSC). Research directions center on AI-driven quantum workflows, including deep neural decoders for real-time QEC, AI-assisted noise learning, automated quantum circuit synthesis and optimization, and multi-agent AI systems for executing, decoding, and benchmarking experiments on state-of-the-art quantum hardware and HPC systems. The position offers access to leading quantum hardware and HPC facilities, opportunities to publish in top AI and quantum venues, and the chance to contribute to open-source quantum AI software.\nMajor Duties/Responsibilities:\n\nConduct original research in AI for quantum computing, developing advanced machine learning models, neural decoders for quantum error correction, AI-driven error mitigation, and noise characterization algorithms.\n\nDesign, build, and evaluate AI-assisted quantum workflows, combining deep learning architectures and multi-agent AI systems to automate circuit generation, QEC decoding, and experiment analysis across quantum software frameworks (such as Qiskit, PennyLane, CUDA-Q, Stim) and quantum hardware backends.\n\nDevelop benchmarks and validation methods that test whether AI-generated quantum code, circuits, and analyses are physically and computationally correct.\n\nImplement and benchmark quantum algorithms and error-handling protocols on quantum hardware from multiple providers and modalities, and on GPU/HPC resources, to ground AI systems in realistic device behavior.\n\nPublish in leading peer-reviewed venues, release open-source software, contribute to proposals, mentor students, and collaborate across ORNL and with academic, industry, and national laboratory partners, following ORNL policies for sensitive information and cybersecurity.\n\nBasic Qualifications:\n\nConduct original research in AI for quantum computing, developing advanced machine learning models, neural decoders for quantum error correction, AI-driven error mitigation, and noise characterization algorithms.\n\nDesign, build, and evaluate AI-assisted quantum workflows, combining deep learning architectures and multi-agent AI systems to automate circuit generation, QEC decoding, and experiment analysis across quantum software frameworks (such as Qiskit, PennyLane, CUDA-Q, Stim) and quantum hardware backends.\n\nDevelop benchmarks and validation methods that test whether AI-generated quantum code, circuits, and analyses are physically and computationally correct.\n\nImplement and benchmark quantum algorithms and error-handling protocols on quantum hardware from multiple providers and modalities, and on GPU/HPC resources, to ground AI systems in realistic device behavior.\n\nPublish in leading peer-reviewed venues, release open-source software, contribute to proposals, mentor students, and collaborate across ORNL and with academic, industry, and national laboratory partners, following ORNL policies for sensitive information and cybersecurity.\n\nPreferred Qualifications:\n\nExperience running and benchmarking quantum circuits on real quantum hardware across one or more modalities and providers, such as superconducting (IBM Quantum, IQM), trapped-ion (IonQ, Quantinuum), or neutral-atom (QuEra) platforms, and understanding how device characteristics shape algorithm and QEC performance.\n\nDeep expertise in QEC and AI-driven decoding methods, including neural network decoders for stabilizer codes (such as surface, color, or qLDPC codes), RL- or ML-guided syndrome extraction, and AI-assisted error mitigation strategies (such as probabilistic error cancellation or neural noise learning models).\n\nExperience designing AI-assisted quantum workflows, agentic or multi-agent systems, retrieval-augmented generation (RAG) for scientific domain tasks, or transformer architectures applied to code generation, circuit compilation, and automated scientific discovery.\n\nExperience running large-scale quantum simulations on GPU and HPC systems.\n\nContributions to open-source quantum software, industry research experience, or collaborative research across institutions.\n\nSpecial Requirements:\n\nApplicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.\n\nThis position requires the ability to obtain and maintain an HSPD-12 PIV badge.\n\nFor employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.\nTo obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.\nFor foreign national candidates:\nIf you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.\nLetters of Recommendation:\n\nPlease submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent  with the position title and number referenced in the subject line.\nInstructions to upload documents to your candidate profile:\nLogin to your account via jobs.ornl.gov\n\nView Profile\n\nUnder the My Documents section, select Add a Document\n\nAbout ORNL:\n\nAs a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.\nORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.\nOther benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.\nThis position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.\nWe accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.\nIf you have trouble applying for a position, please email .\nORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. 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