08 University of Illinois at Chicago, United StatesPostdoctoral Fellowship at

The Visiting Research Associate II conducts research by assisting with the collection and documentation of study data from research participants, cleaning of data and other supportive functions to facilitate efficient teamwork in a clinical research environment.

 

This position may supervise junior staff. This position supports the implementation of effective strategies for optimizing the recruitment of research participants and for maintaining their active engagement through to the study’s end. The incumbent works closely with management to ensure those study goals are met and that regulatory compliance is maintained. This position may be undertaken remotely and will be focused on COVID-19 patient engagement by telephone.

The laboratory of Dr. Yuhang Fan in the Department of Biochemistry and Molecular Genetics in the College of Medicine at University of Illinois Chicago is looking for motivated post-doctoral candidates to study the functions of RNA biochemistry in organismal regeneration. RNA and its chemical modifications are key regulators of cell fate decisions and represent promising functional targets for regenerative medicine. This candidate will work on multiple projects that combine unique model organisms, spatial omics technology development, and computational modeling to uncover RNA-driven mechanisms that enable whole-body regeneration and to identify new epigenetic targets for therapeutic intervention. Interested candidates can visit the faculty member’s publication list: https://scholar.google.com/citations?user=04N7CgMAAAAJ and read the most recent publications.

This position will focus on the atomic-resolution characterization of CdSeTe-based solar cell materials using aberration-corrected scanning transmission electron microscopy imaging, especially 4D-STEM, and electron spectroscopy. The work will be carried out using UIC’s aberration-corrected cold field-emission JEOL ARM200CF and the ThermoFisher Helios 5CX focused ion beam/scanning electron (FIB-SEM) microscope. The successful applicant will have experience in electron microscopy characterization of CdTe-based solar cell devices, including 4D-STEM, electron ptychography, electron back-scattered diffraction, EDS, and FIB-SEM sample preparation.

Dr. Klie’s Nanoscale Physics Group has access to the UIC Research Resources Center (RRC), which provides a world-class research environment with an array of electron beam instruments and in-situ capabilities, including the aberration-corrected JEOL ARM200CF and Helios 5CX. A successful candidate is expected to work with a team at UIC and partners at the Cadmium Telluride Accelerator Consortium (CTAC).

This position is specific to sickle cell disease research and quality improvement. It includes pre and post research activities, internal and external to the clinical setting.  They help facilitate OSF institutional and IRB approvals for all assigned research projects. They aid in subject recruitment, screening, scheduling, testing, and data management for multi-faceted investigations, as needed. Additionally, they may help coordinate comprehensive patient protocol treatment schedules to maintain compliance to protocol requirements. 

The Immune Imaging group at the University of Illinois Chicago is seeking a postdoctoral research associate to conduct research with the group. The research group specializes in nanoscale immunobiophysics.

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.