Group Leader - Electron and X-ray Microscopy; EXM

Overview

The Group Leader (GL) for the Electron and X-ray Microscopy (EXM) Group at the Center for Nanoscale Materials (CNM) develops, leads, and executes world-class R&D programs in electron and X-ray microscopy, achieving international recognition for scientific excellence. The GL is responsible for ensuring safe, efficient, and impactful user and research operations. This role combines hands-on research with strategic leadership of a multidisciplinary team of scientists and engineers.

The GL advances the frontiers of nanoscience by conceiving, conducting, and disseminating high-impact experimental research. The position plays a central role in strengthening the CNM user science program, with a particular focus on electron microscopy and synchrotron-based X-ray microscopy at the Advanced Photon Source (APS). The GL also contributes to the development of next-generation microscopy methods, instrumentation, and data workflows, while overseeing the group’s day-to-day operations, budget, user science portfolio, and R&D activities.

• Provide scientific, technical, and operational leadership for the Electron and X-ray Microscopy (EXM) Group, ensuring safe, reliable, and effective user operations

• Develop, lead, and execute innovative R&D programs in electron and X-ray microscopy that achieve international recognition and align with CNM and Argonne strategic priorities

• Conduct original research in nanoscience, from concept development through experimental execution, analysis, and dissemination via peer-reviewed publications and presentations

• Manage and mentor a team of scientists, postdocs, and engineers specializing in electron and X-ray microscopy, fostering a collaborative, inclusive, and high-performance culture

• Advance the CNM user science program, enabling cutting-edge experiments in electron microscopy and synchrotron X-ray microscopy at the APS, and ensuring a high-quality user experience

• Drive the development and implementation of advanced microscopy technologies, including:

  • New imaging and spectroscopy modalities

  • Ultrafast and in situ/operando techniques

  • Advanced detector technologies and correlative approaches that reveal structure–function relationships

• Contribute to and enhance data-intensive microscopy workflows, including data management strategies and, where appropriate, AI/ML-enabled experimental design and data analysis

• Oversee day-to-day group operations, including resource allocation, budgeting, scheduling, safety protocols and procedures, and facility planning to support both user and in-house research programs

• Build and sustain strong collaborations across CNM, APS, other Argonne divisions, and external academic and industrial partners

• Communicate group goals, progress, and impact effectively to stakeholders at all levels, and represent the EXM Group and CNM in internal and external forums

Completed applications will be reviewed as received, with all applications submitted by January 30th, 2026, given full consideration. The position will remain open until filled.

• Ph.D. in materials science, physics, chemistry, electrical engineering, or a related field, and 10 years of relevant research experience (post-Ph.D.)

• Considerable knowledge of electron and X-ray microscopy techniques and their application to nanoscience, with strong connections to chemistry, physics, and materials science

• Demonstrated understanding of the complementary and synergistic use of electron and X-ray micros copies to address forefront problems in nanoscience

• Considerable knowledge of the application of nanostructures to key technological areas such as:

  • Quantum science and technology

  • Microelectronics

  • Sensing

  • Energy conversion and storage

• Considerable experience in designing and implementing novel nanotechnologies as they relate to electron and X-ray microscopy, including:

  • Ultrafast and time-resolved methods

  • Advanced detector and instrumentation development

  • Complementary spectroscopies that elucidate structure–property–function relationships

• Knowledge of data management practices and AI/ML approaches for experimental planning, workflow optimization, and data analysis is beneficial

• Advanced…