Company

Wake Forest UniversitySee more

addressAddressNorth Carolina, United States
type Form of workFull Time
CategoryEducation/Training

Job description

Application Instructions:

External Applicants: Please upload your resume on the Apply screen. Your application will automatically populate your resume details, and you may verify and update data on the My Information page.

Please add your cover letterand any other documents required for the position to the Resume/CV document upload section at the bottom of the My Experience application page. Use the Select Files button to add multiple documents including your cover letter and supporting documents. The My Experience page is the only opportunity to add your cover letter and supporting document attachments. You will not be able to modify your application after you submit it.

Current Employees: Apply from your existing Workday account. Do not apply from the website. Log in to Workday. Click on the Jobs Hub and select Browse Jobs. Locate the position and click Apply. Update your Education and Job History.

** Cover letter required for all positions and optional for facilities, campus services, and hospitality positions unless otherwise specified.Job Description SummaryThe Engineering Department at Wake Forest University is seeking applicants for a postdoctoral research fellowship. The selected candidate will work closely with Dr. Hussein Abdeltawab to develop innovative energy management solutions for distributed generators, renewable energy integration, EV charging, and multi-carrier systems. The research will also involve deep Learning applications in wind and solar power forecasting and deep reinforcement learning applications in transportation electrification and multi-carrier energy systems. We are especially interested in candidates with a solid foundation in power systems, power electronics, deep learning, optimization, and control systems applications. The successful applicant will collaborate in preparing presentations and papers for publication in top-tier journals. The selected candidate will also help mentor research assistants and support the development of technical proposals. This position is offered on a one-year contractual basis, with the potential for extension.Job Description

Essential Functions:

  • Develops technical algorithms utilizing advanced deep learning techniques for different power and energy applications.

  • Writes project reports, journal articles, conference papers, and presentations.

  • Builds experimental test systems and simulators to collect data to validate modeling and analysis work.

  • Support in technical proposal preparation for developing new projects.

  • Contributes to the training of undergraduate and graduate research students.

Required Education, Knowledge, Skills, Abilities:

  • PhD in Electrical Engineering or other related engineering discipline.

  • Profound knowledge in power systems modeling, machine learning algorithms, control systems applications, and optimization.

  • Proven track record of publications.

  • Outstanding skills in interpersonal communication, and effective time management.

  • Capability to work independently or in a cooperative team setting.


Preferred Education, Knowledge, Skills, Abilities:

  • Experience with modeling power electronic converters, energy storage systems, distributed generators including wind and solar systems, Electric vehicles, Hydrogen production systems, and transportation networks.

  • Proficiency with using Matlab/Simulink, Python, TensorFlow, Keras, or other deep learning tools.

  • Experience in building Hardware in the loop systems, microgrids, or EV simulators.

Additional Job DescriptionTime Type RequirementFull timeNote to Applicant:This position profile identifies the key responsibilities and expectations for performance. It cannot encompass all specific job tasks that an employee may be required to perform. Employees are required to follow any other job-related instructions and perform job-related duties as may be reasonably assigned by his/her supervisor.In order to provide a safe and productive learning and living community, Wake Forest University conducts background investigations and drug screens for all final staff candidates being considered for employment.Wake Forest seeks to recruit and retain a diverse workforce while promoting an inclusive work environment committed to excellence in the spirit of Pro Humanitate. In adherence with applicable laws and as provided by University policies, the University prohibits discrimination in its employment practices on the basis of race, color, religion, national origin, sex, age, sexual orientation, gender identity and expression, genetic information, disability and veteran status and encourages qualified candidates across all group demographics to apply.
Refer code: 8279064. Wake Forest University - The previous day - 2024-02-21 11:57

Wake Forest University

North Carolina, United States
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