Postdoctoral Research Associate - College of Engineering - Materials Science and Engineering

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here!

As one of the oldest forms of applied science and engineering, Carnegie Mellon University’s Department of Metallurgical Engineering was founded in 1906 and named after its emphasis on the study of metals. Since then, our field has broadened to include all classes of materials from ceramics and polymers to semiconductors and biological materials. Whereas early eras of civilization were widely identified by human’s ability to work with new material (Stone Age, Bronze Age), today our abilities and projects span a variety of materials and combine everything from physics and chemistry to civil and electrical engineering.

The Materials Science and Engineering Department in the College of Engineering is seeking a postdoctoral scholar to join Mohadeseh Taheri-Mousavi’s group. The postdoc will develop and conduct advanced machine learning techniques combined with computational research to study the mechanical behavior of welds.

Responsibilities:

• Expert on steels and steel welding or additive manufacturing
• Develop advanced machine learning framework to combine different modality and fields of data
• Conduct CALPHAD-based simulations in a high-performance computing (HPC) environment
• Perform data analysis and visualization
• Perform machine learning and inverse design techniques
• Train and supervise masters and doctoral students
•  Coordinate research with external collaborators
• Report and present results
• Identify problems and obstacles to progress; develop strategies to tackle problems
• Participate in writing high impact papers, reports, proposals, and training
• Document procedures; curate and preserve data
• Perform other related duties as assigned

Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

Qualifications:

• PhD Degree in MSE/MECHE or a related field (e.g., physics, chemistry, chemical
  engineering)
• Publications in peer-reviewed journals
• Expert in advanced machine learning such as multi-agent generative AI, LLMs, Diffusion models, and traditional machine learning techniques
• Expert in CALPHAD-based ICME techniques
• Expert in combining different numerical tools via Python scripting
• Experience conducting machine learning and inverse design models
• HPC experience
• Experience training and supervising students
• High proficiency in writing skills
• Teamwork, communication, and presentation skills.
• A combination of education and relevant experience from which comparable knowledge is demonstrated may be considered

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance. 

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our