Postdoctoral Fellow in Machine Learning for Materi
at ORAU Workforce Solutions

Date Posted: 5/22/2019

Opportunity Description

Title of Research Opportunity: Postdoctoral Fellow in Machine Learning for Materials The Energetic Materials Science Branch at the Army Research Laboratory has multiple openings for outstanding postdoctoral or senior research fellows in the cross-disciplinary area of machine learning for materials. This research will involve application of machine learning methods to energetic materials and you will perform close collaboration with experts in computational chemistry, computational physics, computational solid mechanics, experimental chemistry, and mechanical engineering. Machine learning and data science efforts have made wide impact in modern chemistry research, but the study of propellants and explosives has not seen significant contribution from work leveraging those techniques. We are pursuing two main problems of interest. One track will focus on the development of machine learned models for chemical reactions relevant to energetic materials, building upon advances in that area relevant to the pharmaceutical industry. The other track will focus on the development of predictive models for propellant and explosive formulation properties, including both performance and physical properties. Candidates may have the opportunity to research both tracks, as according to available time and interest. This research is expected to be published in open literature journals. Seeking postdoctoral candidates as well as Senior Research Fellows with a PhD in one of the following fields: chemistry, physics, biochemistry, computer science, chemical engineering, or mechanical engineering. The candidate must have significant programming experience in one of the following languages: python, Fortran, C, C++, Java. The candidate must be a U.S. citizen. Skill with at least one of the following is preferred, but not necessary: unix / linux, random forests, graph theory, neural networks, kernel ridge regression, Gaussian process regression, git, bash / shell scripting, parallel programming (MPI / OpenMP), organic chemistry, and energetic materials. The candidate should have a track record of publication in peer-reviewed journals or conference proceedings and be able to provide at least two letters of recommendation upon request. This project is located at Aberdeen Proving Ground in Aberdeen, Maryland. Keywords: machine learning, energetic materials, computational, data science, artificial intelligence Click here for more information

Opportunity Snapshot

About Us

Grooming future leaders in science and technology requires enhancing the skills, knowledge and experience of workers early in their careers. To that end, ORAU (Oak Ridge Associated Universities) assists in connecting the best and most diverse students, recent graduates, faculty and professionals with world-class fellowships, internships and jobs, whether in national laboratories, research institutions, federal government offices or private sector R&D departments.

ORAU works with agencies such as the U.S. Army Research Laboratory (ARL) Research Associateship Program (RAP) allow Postdoctoral Fellows, Journeyman Fellows (undergraduate and graduates students and recent graduates), Senior Researchers, and Summer Faculty engage in research initiatives of their own choice, that are compatible with the interests of the government and will potentially contribute to the general effort of the ARL. We work with the Environmental Protection Agency (EPA) to place recent graduates in full-time and part-time jobs in the Office of Research and Development at EPA under the National Student Services Contract. ORAU also works with Center for Medicare and Medicaid Innovation.

Research opportunities include, but are not limited to the following disciplines: Aerospace Engineering, Anthropology, Archeology, Biology, Biochemistry, Biological Engineering, Biomechanical Engineering, Biomedical Engineering, Chemical Engineering, Chemistry, Computer Science, Computer Engineering, Data Science, Electrical Engineering, Environmental Health Risk Assessment, Environmental Science, Entomology, Epidemiology, Ergonomics, Geology, Health Education Mechanical Engineering, Materials Science, Mathematics, Nanotechnology, Photonics, Physics, Public Health Economics, Public Health Policy, Toxicology, and more.

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