Jobs at Argonne National Laboratory

Conduct applied research on next-generation lithium/sodium battery materials: design electrochemical experiments, fabricate prototype electrodes and pouch cells in a dry-room, perform structural and chemical characterization, analyze data, prepare reports and manuscripts, present findings, maintain lab equipment, ensure ESH/QA compliance, and collaborate with internal and external researchers to support program milestones and proposals.

Postdoctoral researcher will develop on-chip superconducting quantum detectors coupling magnetic targets (magnons/YIG) to solid-state qubits for axion dark-matter detection. Tasks include superconducting hybrid circuit design and nanofabrication, microwave and cryogenic characterization, detector demonstration experiments, and development of quantum-limited devices tolerant to magnetic fields (parametric amplifiers, qubits).

Conduct computational and experimental research developing AI and automated workflows to study interfacial processes in electrochemical materials. Develop and apply AI classifiers and optimization schemes, build autonomous experimental campaigns, perform electrochemical measurements and analytical characterization, adapt workflows for automation, and collaborate across interdisciplinary teams.

Develop a massively parallel lattice Boltzmann (LBM) solver using AMReX for exascale systems (Aurora). Create physics-based, flow/geometry-aware adaptive refinement strategies, integrate in-situ visualization and possible ML, and optimize scalability for multi-phase CFD problems.

Conduct design, fabrication, and cryogenic characterization of superconducting devices and multipixel single-photon detectors; develop multiplexed readout architectures; iterate fabrication and readout designs using simulations; perform low-noise measurements and build instrument systems for photon correlation and spectroscopy.

Machine and finish X-ray optical components from single crystals and other materials using grinding, lapping, ultrasonic milling, and polishing. Set up, operate, and maintain optics fabrication equipment, follow blueprints and specifications, document work orders, and provide advanced technical support for complex fabrication and testing problems while collaborating with the APS Optics Group and customers.

Serve as scientific and technical lead for a DOE-wide AI STEM Educator Jam: design AI-enabled scientific challenge frameworks, develop datasets and LLM workflows, train facilitators, support event implementation, coordinate with cross-lab teams, and iterate content based on feedback to ensure scientific integrity and accessibility.

Design, develop, and evaluate agentic AI systems for scientific discovery, integrating agents with simulations, data pipelines, instruments, workflows, and knowledge bases. Build methods for planning, memory, tool use, workflow orchestration, and decision-making. Deploy and scale systems in HPC/distributed environments, assess scientific usefulness, reliability, robustness, efficiency, and safety, and collaborate with multidisciplinary teams to advance Argonne's AI and scientific missions.

Perform advanced synchrotron x-ray experiments to study materials across solid-melt transitions at high pressure-temperature conditions. Implement and optimize BCDI, XPCS, PCI, nano-beam, time-resolved microscopy, PDF, and 3D imaging on upgraded APS/HPCAT beamlines. Drive scientific direction, expand material scope, develop AI/ML data processing and software, and collaborate with HPCAT staff and partner institutions. Two-year fixed-term appointment with potential extension.

Develop, implement, and support hardware and software for synchrotron beamline control, data acquisition, and analysis. Modernize control systems using C/C++ on Linux, Python, Git, embedded controllers, ROS/EPICS, robotics, electronics, and AI/ML for automation. Translate scientific requirements into technical solutions and documentation.

Lead development and execution of a multi‑million‑dollar R&D program advancing stationary energy storage for AI and data centers. Build partnerships, secure funding, translate operational needs into R&D objectives, and oversee teams applying AI/ML, robotic labs, and digital twins to accelerate battery research, manufacturing, and deployment.

Lead and execute advanced synchrotron X-ray experiments (BCDI, Laue, ptychography, XPCS) to quantify defect and interface dynamics in oxides and 2D materials. Design in-situ/operando studies, acquire multimodal datasets, perform quantitative reconstruction and analysis, and collaborate with AI/ML teams to produce interoperable, physics-informed datasets. Publish and present results and work within multi-institutional teams.

Perform mesoscale and macroscale computational modeling of next-generation batteries, implement and run numerical simulations, integrate AI and agentic workflows to accelerate discovery, analyze simulation and experimental data, collaborate with experimental and theoretical teams, publish results, and present findings at conferences.

Support design, development, and integration of ALCF HPC environments. Administer Linux clusters, manage software stacks with Spack, create programming environments (modules/containers), resolve dependency conflicts, maintain compilers and scientific libraries, implement CI and containerized builds, and collaborate with researchers to support scientific computing workloads. Role requires U.S. citizenship and may be filled at junior or more senior technical levels depending on experience.

Postdoctoral researcher to develop, validate, and enhance design methods and models for high-temperature structural materials for nuclear and energy systems. Duties include finite element simulations, constitutive and continuum damage mechanics modeling, reliability and statistical model development, working with engineering design codes, collaborating with staff, and producing technical reports, papers, and conference presentations. On-site at Argonne.

Lead and build an independent research program applying AI, autonomous laboratories, and advanced data-driven methods to accelerate materials and chemistry discovery. Integrate ML pipelines, HPC, and simulation tools, publish results, mentor trainees, and collaborate across multidisciplinary teams while complying with lab safety and security policies.

Conduct research and develop post-training and reinforcement learning methods for scientific foundation models, optimize large-scale training and post-training workflows on leadership-class supercomputers, and collaborate with multidisciplinary teams to apply adaptive learning systems to high-impact scientific problems, publishing and communicating results.

Implement and sustain a CMMS and Configuration Database ecosystem for APS assets. Define asset hierarchies and baselines, integrate CMMS with engineering and operational systems, ensure data governance and configuration integrity, support change control and lifecycle documentation, and enable predictive maintenance and reliability analytics to improve asset performance.

Develop learning-enabled imaging algorithms for 3D reconstruction and real-time adaptive acquisition of noisy synchrotron datasets; implement multimodal alignment and fusion of structural, chemical, and biological signals; collaborate with scientists across computational science, physics, biology, and environmental chemistry to guide experiments and analyze data.

Develop and deploy AI/ML tools for x-ray imaging and autonomous experiments, integrate models into beamline software, build closed-loop workflows and automated pipelines, support on-site user operations, manage metadata and curated datasets, and collaborate with facility AI and computing teams to scale tools for high-throughput tomography and high-speed imaging.