Jr. Specialist in Electrical Engineering

Professor Ayush Pandey in Electrical Engineering is looking for a junior specialist that will develop artificial intelligence (AI) models for applications in physical system modeling, safety evaluation, and system verification, by using Python libraries. The specialist will collaborate with other researchers and students in the area of control theory, artificial intelligence, and mathematical modeling. Duties include literature review of the latest research, analysis of existing methods, working with real-world datasets, evaluating the performance of AI models, and applying mathematical techniques to develop new metrics for AI models.

The successful candidate will have a baccalaureate degree in Electrical Engineering, Computer Science and Engineering, Applied Mathematics, or any other adjacent degree in similar areas is required , or equivalent research experience, e.g., with instrumentation and research equipment, software programs, social science research methods, humanities scholarship, or creative activities. The candidate must be proficient in Python, have experience with training and validation of neural network models and experience in linear algebra and statistical methods demonstrated through coursework and/or research projects.

The successful candidate will also have prior research work on related topics as demonstrated through peer reviewed publications or technical reports; have other output of prior research experience (for example: code repositories, poster presentation); and academic performance in related coursework.

Please provide any relevant experience in the cover letter.

Experience with differential equations and related numerical methods. Experience with programming pipelines for training, validation, and inference of machine learning models in Python (for example, using pytorch or tensorflow) is preferred, or any other similar packages.

In addition applicants that are highly self-motivated individuals, who have demonstrated the ability to conduct scientific research successfully and work independently are desirable.

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As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

"Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.

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The University of California, Merced, is the newest of the University of California system's 10 campuses. With over 9,000 undergraduate and graduate students (https://cie.ucmerced.edu/analytics-hub/student-statistics), UC Merced is committed to interdisciplinary excellence in research and teaching as well as to diversity, equity and inclusion. Ranked as one of the best public universities in the nation by U.S. News and World Report, UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).

The University of California, Merced is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Please refer to the University of California's Affirmative Action Policy and the University of California's Anti-Discrimination Policy.

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