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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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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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The Department of Civil & Environmental Engineering has an opening for a full-time, nine-month, non-tenure track Lecturer to begin in Fall 2025 or Spring 2026. Responsibilities will include a 3/3 teaching load, service roles in assessment and evaluation for program accreditation, and professional development.

This lecturer position will support the University of Houston – Dalian Maritime University (UH-DMU) International Institute in Dalian, China. The Lecturer will teach up to three courses per semester with alternating semesters of online instruction and face-to-face instruction at UH-DMU. When travel is prohibited by State of Texas or US Department of State directives, all instruction will be conducted online. Opportunities for summer teaching online or face-to-face on UH Main Campus may be available on an as-needed basis.

Additional information about the UH-DMU Institute, which delivers University of Houston undergraduate degrees in Civil Engineering, Mechanical Engineering, and Electrical Engineering, can be found

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