Postdoctoral Appointee - NST - Machine Learning for Electronic Structure and Materials Modeling
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7187412 (Ref #: 416696)
- Posting Date: 3 months ago
Job Description
The Midwest Integrated Center for Computational Materials (http://miccom-center.org/) at Argonne National Laboratory and the University of Chicago has an immediate postdoctoral opening in the use of machine learning in electronic structure calculations and advanced sampling. The postdoctoral researcher will work within the groups of Professor Giulia Galli (https://galligroup.uchicago.edu/) and Dr Maria Chan (https://www.anl.gov/profile/maria-k-chan) on developing and applying algorithms and software for the use of machine learning techniques to accelerate the computation of electronic structure properties and experimentally-informed advanced sampling.
Questions should be directed to mchan@anl.gov. Please note that only applications through the Argonne website will be considered.
Postdoctoral appointments are on a one-year basis, with a maximum term of three years, subject to performance evaluation.
MICCoM is a US Department of Energy funded computational materials science software center, involving highly collaborative research to advance computational prediction of materials properties. Argonne National Laboratory offers excellent compensation and benefit packages, and postdoctoral researchers receive extensive career development guidance.
Position Requirements
- A PhD in Computational Physics, Chemistry, Materials Science, Chemical Engineering, or a related field. Degree must have been received within the last 3 years or upcoming year.
- Solid communication and analytical skills
- Ability to work independently and in an interdisciplinary collaborative environment is expected
- Software programming experience is necessary
- Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Applicants should have expertise in some of the following:
Density functional theory modeling of materials, especially in the areas of electronic excitations
Use of artificial intelligence/machine learning (AI/ML) approaches for computational materials problems
Simulation of experimental measurements such as scattering and spectroscopy
Structure search or sampling approaches
Development and implementation of algorithms and software for materials modeling
High-performance and parallel computing
Interested candidates should include with their Workday application:
1. A detailed curriculum vitae including a list of publications and the names and email addresses of three professional references
2. A cover letter, including
description of previous materials modeling experience (techniques, materials, key contributions)
description of AI/ML experience
description of software development experience
3. Expected start date
4. USA citizenship/visa/work eligibility status (if known)
5. One representative publication that best showcases your work
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other 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.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
