PhD position in modeling of the interaction between phase transformations and plasticity

PhD position(s) is available immediately in the Engineering Mechanics program in Aerospace Engineering Department at Iowa State University to perform theoretical and computational part of work on NSF-funded projects on the interaction between phase transformations and plasticity. Phase-field, micromechanical, and macroscale simulations using FEM are of interest, in close collaboration with high-pressure experiments performed in our lab. Please send vita to Prof. Valery Levitas ( vlevitas@iastate.edu ).

Peer Mentor

Application (Word download)


Mechanical Engineering peer mentors work with first-year students who are involved in the Mechanical Engineering Learning Teams (MELTs). Peer mentors are responsible for leading a learning community section in a fast-paced classroom setting for one academic semester (Fall 2021). Responsibilities include classroom management, grading, presenting, and coordinating group activities. The peer mentor position requires passion for Iowa State University and Mechanical Engineering. The position also requires self-motivation, time management, professionalism, innovation, and the ability to work on a team.


  • Cumulative GPA of 3.0 or higher
  • Availability Tuesday and Thursday from 3:10-4:00 during learning community class period
  • Completion of learning community courses with a grade of B or higher
  • Ability to commit to the full Fall 2020 semester, with no co-op/internship commitment
  • Internship and/or study abroad experience is preferred but not required
  • Experience leading students in an academic or extracurricular setting strongly preferred


  • Management of an ME 190 class section of 15-20 students, including:
    • Create daily class plans according to the master MELT schedule
    • Provide a safe and inclusive classroom environment
    • Facilitate classroom discussions, in-class review sessions, help with homework assignments
    • Discuss curriculum and career issues related to mechanical engineering
    • Arrange out-of-class group study sessions, social activities, and meetings
  • Give support to students as they go through academic, social, and professional transitions
  • Grade assignments and update class attendance in a timely manner
  • Maintain appropriate academic and social conduct for the duration of employment
  • Be a positive example to students and be knowledgeable about campus resources
  • Immediately report any classroom issues, student concerns, or problems
  • Communicate frequently with the Learning Community Coordinators and Head Peer Mentors
  • Act with professionalism and responsibility, have patience and a positive attitude
  • Be able to work independently and make decisions that will benefit students

Additional Information

  • Time Commitment
    • 7-9 hours required per week

(2 hours classroom, 4-6 hours class planning/training/staff meetings/class activities)

  • Required to teach all ME 190 class periods and attend all learning community group events
  • Mandatory attendance at staff meetings (weekly) and training meetings
  • Pay rate
  • $10/Hour for Peer Mentor Position
  • $12/Hour for Head Peer Mentor Position

Click here for more info about MELT

Questions? Contact Kirsten Hauge (khauge@iastate.edu)

Postdoc Researcher

A full-time postdoctoral researcher position is immediately available in the System Reliability and Safety Laboratory (SRSL) at Iowa State University.

The postdoc researcher will primarily contribute to a research project on machine learning for the state estimation and lifetime prediction of lithium-ion batteries. Another application domain of interest is the predictive maintenance of rotating machinery (e.g., motors, pumps, and rotor-bearing systems).

Below is a detailed description of this position.


Applications are invited for one Postdoctoral Research Associate position in the Department of Mechanical Engineering at Iowa State University. The research objectives are to (1) develop machine learning algorithms to online detect faults and predict failures of lithium-ion batteries and rotating machinery (e.g., motors, pumps, and rotor-bearing systems) and (2) assist in validating the data analytics on Battery Management Systems (BMS) and Industrial Internet of Things (IIoT) hardware and software platforms. The duration of the position is expected to be one year and may be renewable based on performance and availability of funding. The salary will be commensurate with the prior research experience of the applicant.


Candidates should have a recent Ph.D. in Mechanical Engineering, Electrical Engineering, or a related discipline. Applicants with experience in (1) fault diagnostics and failure prognostics, (2) machine learning and deep learning, and/or (3) experimental/computational studies of lithium-ion batteries are highly encouraged to apply. Particularly, prior research experience in one or more of the following areas are desired:

– Algorithm development for machine learning and deep learning
– Algorithm development for fault diagnostics and failure prognostics
– Algorithm development for battery state estimation in BMS
– Computational modeling of lithium-ion cell designs and their degradation/lifetime
– Vibration analysis for diagnostics/prognostics of rotating machinery


The postdoctoral associate will attend the weekly individual and group meetings, mentor at least two Ph.D. students in the group, and facilitate close collaborations with companies specialized in battery materials design and testing, IIoT, and predictive maintenance. The postdoctoral associate will also publish the findings of his/her research in premier journals, present his/her research in high-impact conferences, and participate in proposal writing. Only individuals who have a strong desire to pursue an academic career are encouraged to apply.

Applicant Information:

The position is available immediately. Applications will be processed as they arrive until the position is closed. Interested applicants should submit by email (1) a cover letter that summarizes prior research experience and (2) a CV to Dr. Chao Hu, chaohu@iastate.edu.