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Argonne National Laboratory · 2 months ago

Assistant Scientist — Data Driven and Autonomous Materials Discovery (CNM)

Lemont, IL

Full-time

Onsite

Mid, Senior Level

$90K/yr - $143K/yr

0+ years exp

Argonne National Laboratory is a premier research facility focusing on nanoscience and nanotechnology. They are seeking an Assistant Scientist to lead and support research in AI/ML, data infrastructure, and materials science, applying advanced methodologies to enhance materials discovery and characterization.

EnergySecuritySocial Impact

Culture & Values

No H1B

U.S. Citizen Only

Responsibilities

Develop and lead an independent and collaborative research program in computational materials science aligned with CNM strategic themes and the DOE mission

Publish in refereed journals and present at conferences, symposia, and seminars

Contribute to proposal development and assist with execution and reporting for CNM, DOE, and other sponsors

Establish and maintain a vibrant, productive collaboration program with CNM users

Provide scientific and technical support for user computational projects to ensure successful execution and growth of user-led research

Support end-users with HPC operations and maintenance issues, job optimization and scheduling, workflow understanding, and software installation

Collaborate with internal and external researchers to drive innovation in nanoscience and nanotechnology

Contribute to CNM’s strategic scientific directions through pioneering R&D

Provide work direction and mentorship to postdoctoral appointees, research assistants, students, and technical staff

Work toward promotion from Assistant Scientist to Scientist

Manage vendor relationships as needed (hardware, cloud, managed support services)

Execute all activities in compliance with Argonne’s ES&H policies, Safeguards and Security policies, work rules, and safe practices

Qualification

AI/ML for predictive modelingComputational materials scienceHigh-performance computingData managementWorkflow designOptimizationCommunication skillsCollaboration in multidisciplinary environmentMentorship

Required

Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Electrical Engineering, or a related field

Proven research track record in computational materials science and AI/ML, with applications in areas such as quantum information science, energy capture/storage/conversion, or microelectronics

Demonstrated ability to formulate scientific problems in the design and theory of nanoscale systems relevant to the DOE portfolio

Considerable skill in data management and high-performance computing, including workflow design and optimization

Strong oral and written communication skills, with the ability to work effectively with internal and external collaborators to achieve established goals

Demonstrated ability to collaborate in a multidisciplinary environment and provide scientific guidance to a diverse research community

Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork