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.

Carnegie Mellon University is currently hiring a Postdoctoral Research Associate to join the College of Engineering. This is an exciting opportunity for someone who thrives in an interesting and challenging work environment. You will contribute to the department by conducting computational research applying CALPHAD-based ICME techniques in combination with machine learning techniques to study the mechanical behavior of alloys in extreme environments.

Your core responsibilities will include:

• Conducting CALPHAD-based simulations in a high performance computing (HPC) environment.

• Performing data analysis and visualization, as well as machine learning and inverse design techniques.

• Training and supervising masters and doctoral students.

• Coordinating research with external collaborators.

• Reporting and presenting results.

• Performing other related duties as assigned.

Flexibility, excellence, and passion are vital qualities within Carnegie Mellon University. Inclusion, collaboration and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who is able to 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.

You should demonstrate:

• Strong verbal and written communication skills

• Ability to work within a team

Qualifications:

• PhD Degree in MSE/MECHE or a related field (e.g., physics, chemistry, chemical engineering) Publications in peer-reviewed journals

• Expert in CALPHAD-based ICME techniques

• Experience conducting machine learning and inverse design models HPC experience

• Python programming

Joining the CMU team opens the door to an array of exceptional benefits, available to all full-time Carnegie Mellon University employees. Experience the full spectrum of advantages, from comprehensive medical, prescription, dental, and vision insurance to enticing retirement savings programs. Unlock your potential with tuition benefits, and take well-deserved breaks with generous paid time off and holidays. Rest easy knowing you are covered by life and accidental death and disability insurance. For a comprehensive overview of the benefits awaiting you, explore:

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At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond just credentials, we consider the role & responsibilities, your invaluable work experience, and the knowledge gained through education and training. We acknowledge and appreciate your unique key skills and the diverse perspectives you bring. Our commitment to fostering an inclusive work environment means we also account for geographic differentials. Your journey with us is about more than just a job; it's about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in this exciting opportunity?! Apply today!

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