Postdoctoral Research Associate

2 weeks ago

Chicago, United States University of Illinois Full time
Postdoctoral Research Associate

Hiring Department: Civil, Materials and Environmental Engineering

Location: Chicago, IL USA

Requisition ID: 1022460

Posting Close Date: Until Position is Filled

About the University of Illinois Chicago

UIC is among the nation's preeminent urban public research universities, a Carnegie RU/VH research institution, and the largest university in Chicago. UIC serves over 34,000 students, comprising one of the most diverse student bodies in the nation and is designated as a Minority Serving Institution (MSI), an Asian American and Native American Pacific Islander Serving Institution (AANAPSI) and a Hispanic Serving Institution (HSI). Through its 16 colleges, UIC produces nationally and internationally recognized multidisciplinary academic programs in concert with civic, corporate and community partners worldwide, including a full complement of health sciences colleges. By emphasizing cutting-edge and transformational research along with a commitment to the success of all students, UIC embodies the dynamic, vibrant and engaged urban university. Recent "Best Colleges" rankings published by U.S. News & World Report, found UIC climbed up in its rankings among top public schools in the nation and among all national universities. UIC has nearly 260,000 alumni, and is one of the largest employers in the city of Chicago.

Description:

Position Summary
Two postdoctoral research associate positions are available in the Multiscale Materials and Manufacturing Laboratory (M3L) at University of Illinois Chicago (UIC). This is a joint position between UIC and Argonne National Laboratory (ANL) seeking fresh PhDs with expertise in computational materials modeling informed machine learning approach development for high-performance computing (HPC) environment. A Ph.D. in appropriate engineering or physical science discipline closely related to this area of research is required. HPC resources at the UIC and ANL will be utilized for massively parallel simulations and training of generative AI models. Physics-informed machine learning approach will be used to predict material evolution under thermomechanical, electro-thermal, and electrochemical conditions. The position will be annually renewable depending on performance with a strong chance for growth, high-impact publications, and opportunities to interact with academia and national labs.

Duties & Responsibilities
Develop multiscale connections of chemistry, mechanical, thermal, and interfacial processes including reactions and degradation with time. One of the projects involves corrosion, and electrochemical reactions in flow environment. The other project involves electro-thermal storage of energy and phase transformations.Perform research activities including setting up molecular scale and atomistic simulations in petascale and GPU environment, analyzing large simulation data, and automating workflow using scripting language such as Python and bash scripts.Assist in the planning, implementation, and evaluation of research projects including identifying project tasks, task assignment, timeline development, monitoring the progress of tasks, and preparing and analyzing activity reports Develop multiscale coupling schemes with uncertainty quantification using Bayesian approach and integrating experiments/simulation in multifidelity materials modeling environment Present research results through reports, technology demonstrations, conference presentations, and the publication of scientific papers, where warranted and desired Assume additional appropriate research related mentoring duties to work with graduate students as needed

Qualifications:

Minimum Qualifications
  • PhD degree in physics, chemistry, materials science, chemical, mechanical engineering and related engineering disciplines
  • Detailed knowledge of large-scale molecular dynamics simulations with specialization developing high impact results and strong connections to first-principles methods
  • A detailed knowledge on materials science of polymers, coatings, alloys and compounds, material databases, ICME approaches and machine learning methods at scale.
  • Knowledge of mesoscale coarse grained MD and discrete element methods such as DPD or continuum codes for performing CFD or FEA calculations in parallel computing environments.
Preferred Qualifications
  • Experience in building applications by combining different molecular dynamics, reactive flow, and multiphysics computational tools
  • Although we seek fresh PhDs, more experienced candidates will be considered for research scholar or research scientist positions
  • Strong background in molecular dynamics simulations, machine learning tools such as PyTorch/Keras or similar environment is desired; exposure to running jobs in diverse HPC environments for large-scale simulations will be a plus
  • Strong numerical background in the validation of simulation results and uncertainty quantification for multifidelity simulation tools will be a plus
  • Demonstrated proficiency in all forms of communication, along with solid time management, teamwork, data visualization and organizational skills

The University of Illinois System is an equal opportunity employer, including but not limited to disability and/or veteran status, and complies with all applicable state and federal employment mandates. Please visit Required Employment Notices and Posters to view our non-discrimination statement and find additional information about required background checks, sexual harassment/misconduct disclosures, COVID-19 vaccination requirement, and employment eligibility review through E-Verify.

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