Postdoctoral Research Associate (Electrical and Computer Engineering)

University of Arizona

life insurance, sick time

United States, Arizona, Tucson

Apr 02, 2025

Postdoctoral Research Associate (Electrical and Computer Engineering)
Posting Number	req22179
Department	Electrical and Computer Engr
Department Website Link	https://ece.engineering.arizona.edu/
Location	Main Campus
Address	1230 E. Speedway Blvd., Tucson, AZ 85721-0104 USA
Position Highlights	The department of Electrical and Computer Engineering (ECE) at the University of Arizona is seeking a qualified and highly motivated Postdoctoral Research Associate with background on AI and machine learning for working on multi-modal image synthesis, including SAR, SONAR, and EO/IR. The successful candidate will work under the direction of Dr. Abhijit Mahalanobis at the University of Arizona. His group is actively conducting research in AI/ML methods for small object detection, discrimination and classification as well as in generative techniques for multi-modal images. The incumbent will contribute to novel algorithm development, detailed performance characterization and analysis, and trade studies involving these topics. Over the years, Dr. Mahalanobis and his team have worked on methods for Automatic Target Recognition, learning with less data, out of distribution detection, aspects of continuous learning, knowledge merging, as well as other theoretical topics on the fundamentals of AI/ML. We invite qualified candidates to join our group and participate in cutting-edge research related to these topics. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.
Duties & Responsibilities	Conduct research on generative and discriminative deeplearning techniques for synthetic aperture radar imagery. This includes 1) Deep component analysis for information processing, 2) physics based generative models for end-to-end imaging, and 3) multi-modal/multi-sensor/multi-band super resolution data generation and fusion. Foster collaborations in AI/ML research within the Department, with other units across the University, and with team members at other institutes. Participate in meetings with industry sponsors. Present research at national and international conferences. Prepare manuscripts for publication in peer-reviewed journals. Participate in grant writing, including generating preliminary data, submitting grant applications, and preparing progress reports. Additional duties as assigned. Knowledge, Skills and Abilities: Knowledge of deep learning, machine learning, image processing, and EO/IR and RF signal processing. Strong analysis skills, research, and technical writing skills. Ability to communicate professionally in a clear, concise manner orally and in writing.
Minimum Qualifications	PhD degree in Electrical Engineering, Electrical and Computer Engineering, Computer Science, or a related field of study. Selected applicant must have PhD conferred upon hire.
Preferred Qualifications	Two years of prior work experience in small business R&D is preferable. Experience in deep learning tools in Matlab and Python/Pytorch, familiarity with computing platforms for AI/ML, and programming in python or C/C++.
FLSA	Exempt
Full Time/Part Time	Full Time
Number of Hours Worked per Week	40
Job FTE	1.0
Work Calendar	Fiscal
Job Category	Research
Benefits Eligible	Yes - Full Benefits
Rate of Pay	NIH salary guidelines, Depends on Experience
Compensation Type	salary at 1.0 full-time equivalency (FTE)
Type of criminal background check required:	Name-based criminal background check (non-security sensitive)
Number of Vacancies	1
Target Hire Date	5/26/2025
Expected End Date
Contact Information for Candidates	Dr. Abhijit Mahalanobis amahalan@arizona.edu
Open Date	4/1/2025
Open Until Filled	Yes
Documents Needed to Apply	Curriculum Vitae (CV), Cover Letter, and One Additional Document
Special Instructions to Applicant	Please include a short statement of interest describing your background and experience, and how it will enable you to succeed in this position.
Notice of Availability of the Annual Security and Fire Safety Report	In compliance with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University's campuses.Thesereports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures. Paper copies of the Reports can be obtained by contacting the University Compliance Office at cleryact@arizona.edu.