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The Department of Aerospace Engineering at Auburn University invites applications for a non-tenure-track Lecturer position. The primary responsibility for this position will be teaching a selection of undergraduate courses in the field of aerospace engineering, such as aerodynamics, aerospace design, aerospace systems and controls, flight dynamics, structures, orbital mechanics, and propulsion. The teaching of general engineering courses relevant to aerospace engineering, such as statics and dynamics, is also anticipated. 

The successful candidate will bring experience, innovation, enthusiasm, technology, and leadership to the courses. Under typical circumstances, the teaching load will be three courses per semester, which includes course and laboratory development and management activities. In addition to instructional duties, successful candidates will contribute to the instructional mission of the department through participation on faculty committees and be expected to mentor students through possible participation in student 
organizations, competition activities, and other mentoring and knowledge enhancement

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In-brief analysis

May 22, 2025

Data source: U.S. Energy Information Administration, Gasoline and Diesel Fuel Update, and the U.S. Bureau of Labor Statistics
Note: Real prices are adjusted to May 2025 dollars.

The retail price for regular-grade gasoline in the United States on May 19, the Monday before Memorial Day weekend, averaged $3.17 per gallon (gal), 11% (or 41 cents/gal) lower than the price a year ago. After adjusting for inflation (real terms), average U.S. retail gasoline prices going into Memorial Day weekend are 14% lower than last year, largely because crude oil prices have fallen.

Memorial Day weekend is one of the biggest travel weekends of the year, and many of those travelers will go by car. The American Automobile Association (AAA) expects 39.4 million people will travel by car over Memorial Day weekend this

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Research Opportunities

COMPUTER SCIENCE – Artificial Intelligence

Work description

1) Hybridization of physics-based modelling and AI to create decision-support models for human operators under forecast uncertainty.

2) Distributed learning algorithms and coordination strategies to achieve a global goal where, for instance, aspects such as energy consumption (green AI) is covered by testing their implementation in edge devices.

3) Validate the developed methodologies on real data and different use cases focused on energy transition.

4) Dissemination of the work in international journals and/or conferences

Minimum profile required

Previous academic background in applied mathematics or computer science or informatics or electrical engineering or similar.

Preference factors

Past experience (or academic background) with supervised and reinforcement learning. Academic background in operations research. Programming knowledge in Python.

Maintenance stipend: € 1040.98 or 1309.64, according to the table of monthly maintenance stipend for FCT grants ,

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