Postdoctoral Research Associate|Machine Learning/Artificial Intelligence for Additive Manufacturing

Title: Postdoctoral Research Associate Machine Learning/Artificial Intelligence for Additive Manufacturing Employee Classification: Postdoctoral Research Associate Campus: University of North Texas Division: UNT-Research & Innovation SubDivision-Department: UNT-Research & Innovation Department Department: UNT-Ctr Agile & Adaptive Add.Mfg-190405 Job Location: Denton Salary: Compensation is competitive and commensurate with the candidate's qualifications, experience, and discipline, in accordance with university guidelines and available funding.

FTE: 1.00

Retirement Eligibility: ORP Eligible About Us - Values Overview Welcome to the University of North Texas System. The UNT System includes the University of North Texas in Denton and Frisco, the University of North Texas at Dallas and UNT Dallas College of Law, and University of North Texas Health Fort Worth. We are the only university system based exclusively in the robust Dallas-Fort Worth region. We are growing with the North Texas region, employing more than 14,000 employees, educating a record 49,000 students across our system, and awarding nearly 12,000 degrees each year. We are one team comprised of individuals who are committed to excellence, curiosity and innovation. We are transforming lives and creating economic opportunity through education. We champion a people-first values-based culture where We Care about each other and those we serve. We believe that we are Better Together because we foster an environment of respect, belonging, and access for all. We demonstrate Courageous Integrity through setting exceptional standards and acting in the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our UNT System team. Learn more about the UNT System and how we live our values at Department Summary CAAAM is the Center for Agile and Adaptive Additive Manufacturing. CAAAM looks at additive manufacturing, which includes materials, science, cybersecurity, data analytics, logistics, and supply chain. Established in 2019 by the Texas State Legislature with $10 million in funding and recently renewed through 2025, CAAAM conducts next-generation research, education, and workforce training in additive manufacturing. CAAAM's Institute for Transformative Education in Additive Manufacturing-or ITEAM provides courses, seminars, workshops, symposia, in-lab training sessions, and summer camps for industry and community colleges. UNT is rapidly expanding its Center for Agile and Adaptive Manufacturing (CAAAM) (caaam.unt.edu), a State of Texas funded multi-million-dollar initiative with a multi disciplinary focus on further advancing the science and technology of additive manufacturing (AM). CAAAM involves a multi-disciplinary team of researchers from materials science, mechanical engineering, manufacturing, data science, cybersecurity and logistics & supply chain, committed to collaborating on large research projects with an emphasis on additive manufacturing. One of the focus areas of CAAAM is Data Science/Analytics (Machine Learning, ML/Artificial Intelligence, AI) in the context of advanced manufacturing systems in general and additive manufacturing systems more specifically. UNT has a highly diverse campus with a wide range of languages spoken in addition to English. We welcome candidates who have experience with HSI/MSIs and/or who speak Spanish, Vietnamese, American Sign Language, Chinese (Cantonese, Mandarin and other variations), Arabic, Tagalog, Farsi, French, or/and Yoruba. Position Overview This PostDoctorate Research Associate (PDRA) role is primarily focused on the independent technical delivery of and leadership in the development of projects/activities related to ML/ AI in AM within CAAAM. The PDRA will work with the faculty across various departments with interdisciplinary approach to AM. The primary responsibility of this position is to develop digital manufacturing capabilities using ML/ AI learning approaches in AM. The PDRA will provide solution concepts and develop, integrate and implement data driven approaches (experimental dataset physics based model dataset) to achieve process optimization, defect prediction and property prediction in various AM processes. The additional specific capabilities highly desired of the candidate include but not limited to: experience in ML/ AI approaches, application of ML/AL in image processing, reasonable understanding of science/physics and engineering of AM processes for metallic systems, knowledge and experience in heat transfer/fluid dynamics/structural mechanics through the applications of computational and statistical methods. The position is also expected to provide technical expertise and support to graduate and undergraduate students, assist/lead preparation of research proposals and scientific/technical papers and presentations. Minimum Qualifications Earned doctorate in mechanical engineering or materials science and engineering or physics or a related discipline with a research focus on ML/ AI in materials processing/manufacturing. Record of publications related to Machine Learning/Artificial Intelligence for Additive Manufacturing. Preferred Qualifications Applicants that demonstrate aptitude and experience in interdisciplinary collaborations will be a plus. Required License/Registration/Certifications Job Duties Conduct experiments, gather data, document research notes, code and analyze data, interpret data. Prepare manuscripts for publications in a timely manner and talks and posters for presentation at group meetings and conferences. Assist with reporting of research progress to funding agencies. Keep up with historical and latest research data and publications. Stay up-to-date with all trainings, and federal, state, university and department requirements. Physical Requirements Communicating with others to exchange information. Lifting and Moving objects up to 20 pounds. Environmental Hazards Small and/or enclosed spaces. Work Schedule Varies based upon assignment Driving University Vehicle No Security Sensitive This is a Security Sensitive Position. Special Instructions Applicants must submit a minimum of two professional references as part of their application. If needed, additional references can be added after the application has been submitted. EEO Statement The University of North Texas System is firmly committed to equal opportunity and does not permit -and takes actions to prevent - discrimination, harassment (including sexual violence, domestic violence, dating violence and stalking), and retaliation on the basis of race, color, religion, national origin, sex, age, disability, genetic information, or veteran status in its application, employment practices, and facilities; nor permits race, color, national origin, religion, age, disability, veteran status, or sex discrimination and harassment in its admissions processes, and educational programs and activities. UNT System Administration promptly investigates complaints of discrimination, harassment, and related retaliation and takes remedial action when appropriate. System Administration also takes actions to prevent retaliation against individuals who oppose any form of harassment or discriminatory practice, file a charge or report, or testify, assist, or participate in a related investigation or proceeding. #J-18808-Ljbffr University of North Texas