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What are the key skills and qualifications needed to thrive as an Intern in Computational Materials Science, and why are they important?

To thrive as an Intern in Computational Materials Science, you need a solid background in materials science, physics, or engineering, along with coursework in computational modeling and data analysis. Familiarity with programming languages like Python or MATLAB, experience with simulation software (such as VASP or LAMMPS), and knowledge of high-performance computing are typically required. Strong analytical thinking, attention to detail, and effective teamwork are important soft skills for success in collaborative research environments. These skills enable interns to contribute meaningfully to research projects, analyze complex materials data, and communicate findings clearly within multidisciplinary teams.

What types of projects can an Intern in Computational Materials Science expect to work on during their internship?

As an Intern in Computational Materials Science, you can expect to engage in projects involving simulations of material properties, data analysis from computational experiments, and the development of models to predict material behavior. You may collaborate with researchers and senior scientists to support ongoing investigations or help optimize simulation workflows. These projects often require proficiency in programming languages such as Python or MATLAB and may involve the use of specialized software like VASP or LAMMPS. The experience provides a hands-on understanding of how computational methods contribute to advancing materials research and often includes opportunities to present your findings to the team.

What does an Intern in Computational Materials Science do?

An Intern in Computational Materials Science assists in research and development by applying computational techniques to study and predict the properties and behaviors of materials. Typical tasks include running simulations, analyzing data, and working with software tools to model materials at the atomic or molecular level. Interns may collaborate with researchers to design experiments, interpret results, and contribute to scientific publications or reports. This role provides hands-on experience in both computational methods and materials science, helping to bridge theory and practical application.

What is the difference between Intern Computational Materials Science vs Intern Materials Engineering?

AspectIntern Computational Materials ScienceIntern Materials Engineering
Required CredentialsUndergraduate or graduate in materials science, physics, or related fields; basic programming skillsUndergraduate or graduate in materials engineering, mechanical engineering, or related fields; foundational technical knowledge
Work EnvironmentResearch labs, computational modeling, data analysisDesign, testing, and development in labs or manufacturing settings
Industry UsageResearch institutions, tech companies, aerospace, academiaManufacturing firms, product development, construction

Intern Computational Materials Science focuses on computational modeling and simulations of materials properties, while Intern Materials Engineering emphasizes practical design, testing, and application of materials. Both roles require a background in materials-related fields but differ in their core activities and work environments.

What are the most commonly searched types of Computational Materials Science jobs in Illinois? The most popular types of Computational Materials Science jobs in Illinois are:
What are popular job titles related to Intern Computational Materials Science jobs in Illinois? For Intern Computational Materials Science jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Intern Computational Materials Science jobs in Illinois look for? The top searched job categories for Intern Computational Materials Science jobs in Illinois are:
What cities in Illinois are hiring for Intern Computational Materials Science jobs? Cities in Illinois with the most Intern Computational Materials Science job openings:
Intern Computational Materials Science jobs near you
Assistant Scientist - Data Driven and Autonomous Materials Discovery (CNM)

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

Argonne National Laboratory

Lemont, IL • On-site

$90.06K - $143.01K/yr

Full-time

Posted 21 days ago

Job description

The Theory and Modeling Group at the Center for Nanoscale Materials (CNM) seeks an outstanding Assistant Scientist to lead and support frontier research at the intersection of AI/ML, data infrastructure, autonomous systems, and materials science. You will develop and apply advanced data-driven methodologies to accelerate discovery in materials design, characterization, and synthesis. The role combines self-directed and collaborative research aligned with CNM strategic themes, alongside scientific support for CNM users.
CNM is a DOE Office of Science user facility that provides researchers worldwide with world-class expertise and instrumentation for multidisciplinary nanoscience and nanotechnology. Learn more about CNM themes at: https://cnm.anl.gov
Focus Areas (expertise in one or more is highly desirable)
  • AI/ML for predictive modeling and inverse design of nanomaterials
  • Autonomous laboratories for materials synthesis and characterization
  • Generative models, reinforcement learning, and agent-based approaches to streamline experimentation and accelerate discovery
  • Integration of HPC, data infrastructure, and ML pipelines for data-driven and autonomous research
  • Digital twins and simulation-augmented AI tools
  • Interfacing AI tools with experimental facilities at CNM and Argonne

Key Responsibilities
Research leadership (50%)
  • 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

User program engagement (50%)
  • 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

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

Collaboration and mentorship
  • 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

Professional growth and operations
  • Work toward promotion from Assistant Scientist to Scientist
  • Manage vendor relationships as needed (hardware, cloud, managed support services)

Safety, security, and stewardship
  • Execute all activities in compliance with Argonne's ES&H policies, Safeguards and Security policies, work rules, and safe practices

Position Requirements
  • 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

How to Apply Submit the following materials via the Argonne National Laboratory careers portal:
  • Cover letter detailing how your experience and expertise align with and will contribute to this position
  • Curriculum vitae with publication list and contact information for three professional references
  • 2-page research statement outlining proposed research directions
  • 1-page statement describing your approach to engaging and growing the CNM scientific user program

RD2: Bachelors and 5+ years of experience, Masters and 3+ years, or PhD and 0+ years, or equivalent
Job Family
Research Development (RD)
Job Profile
Materials/Ceramics/Metallurgical 2
Worker Type
Regular
Time Type
Full time
The expected hiring range for this position is $90,063.00 - $143,010.27.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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