Job ID: 185780

Research Assistant Professor - Additive Manufacturing with Emphasis on Data Science and Analytics and Computational Process Modeling

University of North Texas

  • May 16, 2022
 
  • Research Assistant Professor - Additive Manufacturing with Emphasis on Data Science and Analytics and Computational Process Modeling
  • UNT-Ctr Agile & Adaptive Add. Mfg-190405
  • University of North Texas
    Denton, TX
 
  • Open until filled
  • Available immediately
  •  
 
  • Research Professor
    Assistant Professor
  • Manufacturing & Quality Engineering
 
 

Department Summary UNT is rapidly building its Center for Agile and Adaptive Manufacturing (CAAAM), 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 was established in 2019 and has evolved into a comprehensive research facility (https://caaam.unt.edu/). CAAAM involves a multi-disciplinary team of researchers from materials science, mechanical engineering, manufacturing, data science, cybersecurity, and logistics & supply chain management, committed to collaborating on large research projects with an emphasis on additive manufacturing. Specifically, data science & analytics and physics-based AM process modeling for its thermokinetic effects on materials in the context of advanced manufacturing systems in general and additive manufacturing systems more specifically continue to be emphasis of CAAAM activities.

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 Summary The Center for Agile and Adaptive Manufacturing (CAAAM) is seeking a Research Assistant Professor to collaborate with a team of faculty on issues related to AM. This is a non-tenure track predefined terms faculty position with a primary association with CAAAM and secondary association jointly with the Department of Mechanical Engineering and Department of Materials Science & Engineering, College of Engineering. The selected research faculty is expected to focus on data science & analytics and physics-based AM process modeling for its thermokinetic effects on materials in the context of advanced manufacturing systems in general and additive manufacturing systems particular. A successful candidate will work closely with the CAAAM associated faculty and researchers in multidisciplinary areas complementary to advanced/additive manufacturing. The candidate is also expected to develop educational material for training skilled workforce to operate advanced manufacturing systems as well as mentor graduate students and post-doctoral researchers working in CAAAM.

Minimum Qualifications
An earned doctorate in, Mechanical Engineering or Materials Science & Engineering or a related discipline with a research focus on data science and analytics and computational modeling of thermokinetics related transformations during AM.

Preferred Qualifications
Experience working with industry members in related areas with applications in manufacturing is preferred. The research background should be evident from high quality publications. Applicants that demonstrate aptitude and experience in interdisciplinary collaborations will be a plus.


 
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