Create and release your Profile on Zintellect – Postdoctoral applicants must create an account and complete a profile in the on-line application system. Please note: your resume/CV may not exceed 2 pages.
Complete your application – Enter the rest of the information required for the IC Postdoc Program Research Opportunity. The application itself contains detailed instructions for each one of these components: availability, citizenship, transcripts, dissertation abstract, publication and presentation plan, and information about your Research Advisor co-applicant.
Additional information about the IC Postdoctoral Research Fellowship Program is available on the program website located at: https://orise.orau.gov/icpostdoc/index.html.
If you have questions, send an email to ICPostdoc@orau.org. Please include the reference code for this opportunity in your email.
Research Topic Description, including Problem Statement:
The interest in utilizing theoretical science to predict new materials and synthesis pathways has been longstanding. Computing power has accelerated in the 21st century and corresponding advancements in artificial intelligence (AI) and machine learning (ML) have increased. Recent research is applying AI, ML, and autonomous systems to the field of chemical synthesis. At present, human-led discovery of new materials through manual practices can take decades of research, significant continuous funding, and can result in a high degree of risk. This fellowship would focus on applying ML for the discovery of novel materials to increase efficiency and reduce cost and risk.
Recent research across academia has led to the creation of software to translate bulk text into low-level instructions using natural language processing1. Development in this space allows for the optimization of experiments based on prior experiences and the progress of data-driven materials discovery2. This problem statement is specifically looking at the next stage of the pipeline to identify, implement, and validate a method for machine-led discovery of materials. This may include the discovery of novel materials or the discovery of novel reaction pathways for conventional or traditional materials. Research in this area would also enable the assurance of material supply and identification of potential new material threats.
1 ChemData Extractor: A Toolkit for Automated Extraction of Chemical Information from Scientific Literature, M. Swaine, J. Cole, https://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00207
2 A Design-to-Device Pipeline for Data-Driven Materials Discovery, J.Cole, https://pubs.acs.org/doi/10.1021/acs.accounts.9b00470
Example Approaches:
Proposals should include the assessment and development of available algorithms for discovery of new materials using ML. These should be assessed against the following criteria:
The most relevant and applicable method(s) should be implemented and validated against applicable data.
Open-source datasets for model training are available. These include but are not limited to:
The Cambridge Structural Database (https://www.ccdc.cam.ac.uk/structures/) may also be used; however, this is licensed. It is expected that datasets from different sources may be required to best train a model for a variety of scenarios.
Proposals are also invited to consider future developments in the pipeline such as in-line characterization (e.g. in chemical synthesis) and analysis of predictions.
Technical collaborating from the ML and chemical synthesis aspect will be offered. In addition, classified data will be used for testing of models, and validation and feedback will be provided for further development.
Relevance to the Intelligence Community:
Machine led discovery has applications across the Intelligence Community, including:
This is a vital stage in the discovery, manufacture, and validation pipeline, alongside enhancing materials assurance. Ultimately, this research will enable the discovery of materials beyond human capability. In the future, this capability would also enable the screening of materials that do not obey conventionally understood chemistry and classification. Successful developments would lead to integration with robotics and automated manufacture.
This research has the potential to be used in the domains of pharmaceuticals, synthetic biology, advanced materials, and more.
Key Words: Machine Learning, ML, Artificial Intelligence, AI, Neural Networks, Automated Discovery, Novel Materials, Automated Chemical
You gave a rating of 0 star(s)
SECURITY/PRIVACY NOTICE
By continuing to use this system you indicate your awareness of and consent to the following terms and conditions of use. LOGOUT IMMEDIATELY if you do not agree to the conditions stated in this warning.
SECURITY NOTICE
This system is part of a Federal information system. This system is monitored for security purposes to ensure it remains available to all users and to protect information in the system. The system employs software programs to monitor network traffic to identify unauthorized activities. By accessing this system, you are expressly consenting to these monitoring activities. Unauthorized attempts to defeat or circumvent security features; to use the system for other than intended purposes; to deny service to authorized users; to access, obtain, alter, damage, or destroy information; to upload or change information; to otherwise cause system or information damage; or otherwise to interfere with the system or its operation, is prohibited. Evidence of such acts may be dis-closed to law enforcement authorities and result in prosecution under the Computer Fraud and Abuse Act of 1986 and the National Information Infrastructure Protection Act of 1996, or other applicable laws.
PRIVACY NOTICE
This system is for authorized use only. Use of this system constitutes consent to security monitoring and testing. All activity is logged with your host name and IP address. Users (authorized or unauthorized) have no explicit or implicit expectation of privacy. Any or all uses of this system and all files on this system may be intercepted, monitored, recorded, copied, audited, inspected, and dis-closed to authorized site and law enforcement personnel, as well as authorized officials of other agencies, both domestic and foreign. By using this system, the user consents to such interception, monitoring, recording, copying, auditing, inspection, and disclosure at the discretion of authorized site or law enforcement personnel. Unauthorized or improper use of this system may result in administrative disciplinary action and civil and criminal penalties.
You have been inactive on this page for . You will be logged out after 03:00:00.
Select an icon below to visit the website and download an appropriate browser.
For help, please email Zintellect@orau.org.
Question: What is the deadline for submitting an application?
Answer: Not all opportunities have application deadlines. Some opportunities remain open until they are filled. If an opportunity has an application deadline, then it will be listed in the opportunity details or in the opportunity catalog.
Question: How do I reset my password?
Answer: If you have forgotten your password or wish to reset your password, use the "Forgot password or username?" tab on the login to reset it.
Question: I forgot my username. How do I retrieve it?
Answer: Use the "Forgot password or username?" tab on the login. You will receive an email containing your username.
Question: What do I need to submit an application?
Answer: Typically, applicants are required to submit a resume or CV, an official copy of their transcripts or academic record, and a minimum of two references at the time they apply. Additional requirements such as a writing sample, thesis or dissertation, etc. may be required. Review the opportunity details for additional information about the requirements for applying for an opportunity.
Question: Where do I upload my transcripts?
Answer: If required, you will be asked to upload your transcript as a part of the application process.
Question: Where do I submit a writing sample?
Answer: If required, you will be asked to upload a writing sample as part of the application process.
Question: Can a family member serve as a reference?
Answer: No; family members may not serve as references. References must be able to speak to your educational and/or professional experience. At least one academic reference is preferred.
Our Zintellect A.I. is constantly learning how to Match you to our opportunities! So, we want to know when we get it right or when we get it wrong. This will help us make our better! Plus, as a potential applicant to one of our many opportunities across the country, we value you and want to help you on your career path!
