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A fully supported PhD position on Machine Learning for Scientific Computing is available in the Department of Mechanical and Aerospace Engineering at Rutgers University. The successful applicant will work under the supervision of Dr. George Moutsanidis and the desired start date is January 2026.

The PhD project will focus on the development and application of advanced machine learning techniques on computational fluid dynamics and computational solid mechanics. This includes both data-driven and physics-informed approaches, with potential applications in optimization, surrogate modeling, and uncertainty quantification.

Required Qualifications:

MS degree in Engineering, Applied Mathematics, or related field Solid academic background in the theory and application of novel machine learning techniques, such as, deep operator networks, graph neural networks, and generative AI methods. Solid academic background on scientific computing Excellent coding skills Exceptional analytical and problem-solving skills Strong communication and teamwork capabilities

Why join Rutgers

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About the Job

The Department of Aerospace Engineering & Mechanics (AEM) at the University of Minnesota seeks applicants for the position of Department Head.

The successful candidate should be an experienced and visionary leader with a deep commitment to both research and academic excellence to serve as the next Department Head. The department currently has 20 full-time faculty members with approximately 240 undergraduate and 80 graduate students. The department maintains a vigorous and diverse research portfolio with an annual research expenditure of $14M.

AEM seeks a Department Head who will further enhance our position as a leader in research and education. The successful candidate will possess strong leadership and management abilities. They will have a deep commitment to promoting sponsored research programs, mentoring faculty, broadening the department’s engagements with the local and national aerospace industries, and maintaining our excellence in undergraduate and graduate education.

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Requirements for the candidate

Solid background in Engineering, with a PhD or DSc in Mechanical / Materials Engineering or related areas.

Expected skills and background:

•  ability to collect and critically analyze the state of the art related to the project needs;

•  organizational, planning and communication skills – oral and written, in Portuguese and English;

•  adaptability to the project needs, with a strong appreciation for teamwork;

•  background on physical and chemical properties of polymeric materials and their applications to structures subject to offshore environment;

•  knowledge of experimental characterization of mechanical properties of dielectric materials, with understanding of their behavior and long-term failures risks;

•  skills in modeling structures and knowledge of structural mechanics, preferably applied to offshore structures;

•  background on finite element computational tools;

•  background on programming languages, preferably Python; knowledge of object orientation is desirable.

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Job ID: 259762

Coord, Engineering Research Data & AI Development
Auburn University Job Summary

The Coordinator, Research Data and AI Development plays a pivotal role in advancing the research capabilities of the College of Engineering by developing and implementing Artificial Intelligence (AI)-driven tools and datacentric solutions. This position supports strategic decision-making and fosters innovation, ensuring the College keeps pace with the rapid, exponential growth of its research enterprise. In collaboration with faculty, researchers, and leadership, the Coordinator leads efforts to design, optimize, and deploy cutting-edge AI applications that enhance research methodologies, streamline data management, and provide actionable insights for institutional advancement. The role involves overseeing data strategy, maintaining robust research infrastructure, and ensuring compliance with best practices in AI and data governance.

Essential Functions Development and Coordination of AI-Driven Research Tools: Designs,

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