Postdoctoral Appointee - ML/AI for X-ray Scattering to Enhance Structural Resolution
Argonne National Laboratory
Lemont, USA
Job posting number: #7293232 (Ref:419185)
Posted: November 7, 2024
Job Description
The Chemical and Materials Science group in the X-ray Science Division is seeking a highly motivated Postdoctoral Appointee. X-ray scattering is a key technique at the Advanced Photon Source (APS), widely utilized for characterizing biomacromolecules, polymers and other nano-scale structures.
The successful candidate will join an interdisciplinary team and leverage machine learning or artificial intelligence (ML/AL) algorithms and other computational methods to enhance the structural resolution of current X-ray scattering techniques. This position offers the opportunity to work at state-of-the-art X-ray scattering beamlines at APS and apply the developed methods for detailed structural characterization.
Position Requirements
This level of knowledge is typically achieved through a formal education in Physics, Biophysics, Physical Chemistry, or a related field at the PhD level with zero to five years of employment experience.
Experience with scientific programing.
Excellent oral and written communication skills.
Ability to collaborate effectively in an interdisciplinary research team setting.
Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Ability to understand, value, and promote diversity, equity, inclusion, and accessibility.
Preferred Knowledge, Skills and Experience
Experience with biomolecular Molecular Dynamics Simulations.
Familiarity with Machine Learning / Artificial Intelligence.
Familiarity with standard data science and machine learning python libraries.
Hands-on experience with X-ray scattering techniques.
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.
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