|Published||January 31, 2023|
|Location||Dayton, United States of America|
This job announcement will be accepting candidate submissions until 1700 EST on 13 February 2023. Position is open to all US citizens. The AFRL Materials and Manufacturing Directorate seeks to hire a motivated Materials or Research Scientist or Engineer with Machine Learning or Artificial Intelligence experience to serve as a Researcher in the Metals Branch of the Composite, Ceramic, Metallic and Materials Performance Division. This position will be filled at the DR-2 (GS-12/13 equivalent) level and is located at Wright-Patterson Air Force Base in Dayton, OH. This position may be filled as a 5-year Modified Term Appointment (new government hires, current government term employees, etc.) with the option to later convert to a permanent appointment.
NOTE: Must use MM/DD/YYYY date format for experience entries on resume.
For resume writing tips, facts about the federal hiring process and additional resources, visit: https://www.usajobs.gov/Help/faq/application/documents/resume/what-to-include/
Position duties include, but are not limited to:
- Utilize machine learning (ML) and artificial intelligence (AI) techniques to deepen materials understanding for metals and to answer previously unanswerable questions to support United States Air Force (USAF) and United States Space Force (USSF) materials development.
- Develops and executes ML/AI tools to evaluate material properties. Works with teams to evaluate materials data and better understand its performance.
- Leads, programs, and conducts in-house research, analyzes data to better understand the behavior and response of metals to validate and verify the efficacy of evaluation tools.
- Plans and executes development programs to enhance the current state-of-the-art for metals development and behavior
- Identify emerging tools and approaches to analyze research data through collaboration with academia, industry, and other government agencies and identify and pursue collaborative research opportunities
- Partner with industry and other government agencies to define near- and far-term science and technology goals to accelerate performance prediction of metals-based systems to meet USAF and USSF requirements.
Yes, this position is eligible for situational telework; as determined by agency policy
Remote Work (CONUS)
No, this position is not approved for remote work.
- US Citizen
- Ability to obtain and maintain a Secret security clearance
- Must have Acquisition Professional Development Program (APDP) Level/Tier 2 (Practitioner) Non-Critical certification in Engineering & Technical Management or obtain within 60 months of assignment
- Must meet, or be capable of meeting Defense Acquisition Work Improvement Act (DAWIA) requirements applicable to the duties of the position
- Possess a professional science or engineering (S&E) degree, in a relevant technical field, from an (ABET) accredited academic institution; if highest earned S&E degree is a Bachelor's, the applicant must also have one year of experience at the DR-01 (GS-07-11 equivalent) level
- Selectee is required to submit annual Confidential Financial Disclosure (OGE Form 450)
COVID-19 Vaccination Requirement: To ensure compliance with an applicable preliminary nationwide injunction, which may be supplemented, modified, or vacated, depending on the course of ongoing litigation, the Federal Government will take no action to implement or enforce the COVID-19 vaccination requirement pursuant to Executive Order 14043 on Requiring Coronavirus Disease 2019 Vaccination for Federal Employees. Therefore, to the extent a Federal job announcement includes the requirement that applicants must be fully vaccinated against COVID-19 pursuant to Executive Order 14043, that requirement does not currently apply.
- Programming experience with programming tools such as: Python, scikit-learn, C/C++, gplearn, seaborn, Dream3D, or physics-based modeling
- Experience with computational material science
- Experience with deep learning, image processing techniques and or statistical methods or data analysis methods
- Good communication skills and ability to glean technical requirements from SMEs to build AF relevant programs
- Masters or Doctorate degree in a relevant technical S&E field obtained from an ABET accredited academic institution
- Experience developing, implementing, and/or using artificial intelligence and machine learning approaches in data modeling or analysis applications
When uploading documents, please utilize the naming convention listed below. The Requisition Number for this announcement is 20514.
- Resume: Req No_Last Name_First Name_Resume
- Transcript: Req No_Last Name_First Name_Transcript
- Latest SF50: Req No_Last Name_First Name_SF50
Acceptable file types: .docx, .pdf