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Field
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, reinforcement learning, and/or wireless communications. The candidate should hold a doctoral degree in electrical or computer engineering or related fields. The successful candidate will have a strong publication
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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/academic , Job ID 56747, to apply. Submit a single PDF including: 1. Cover letter (research achievements, interests, and goals). 2. Current CV. 3. Contact information for three references. Finalists may be
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Engineering, Physics, Electrical Engineering, or closely related fields, and prior experience with CVD thin film growth and characterization. Preferred Qualifications Ph.D. in Materials Engineering, Physics
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://jobs.fsu.edu . If you are a current FSU employee, apply via myFSU > Self Service. Applicants are required to complete the online application with all applicable information. Applications must include all work
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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Computational Neuroscience ● Mathematical/Theoretical Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics
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-Department: UNT-College of Engineering Department: UNT-Mechanical Engineering-130340 Job Location: Denton Salary: Compensation is competitive and commensurate with the candidate’s qualifications, experience
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: PhD in Computer Science, Geographic Information Science, Data Engineering, or a related technical field. Job
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, grant reports, and dissemination of research outcomes in academic and educational technology forums. Mentor undergraduate and graduate students involved in the research project, fostering a collaborative