Veeraraghava Raju Hasti
6 months ago
Scientific Machine Learning for Turbulent Reacting Flow Simulations University of Central Florida in United States
Degree Level
PhD
Field of study
Computer Science
Funding
The position offers a Graduate Research Assistantship (GRA) with a competitive monthly stipend, tuition waiver, and other benefits as per university policies. Access to state-of-the-art lab facilities with cutting-edge computational resources, including GPUs, is provided.
Deadline
Aug 1, 2026
Country
United States
University
University of Central Florida

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Where to contact
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About this position
The Hasti Lab in the School of Modeling, Simulation, & Training within the UCF College of Engineering & Computer Science at the University of Central Florida , USA, is inviting applications for a fully funded PhD position in scientific machine learning for turbulent reacting flows starting in January 2025 (Spring 2025).
Key Responsibilities:
Develop novel energy-efficient, trustworthy, and adaptive scientific machine learning algorithms for turbulent reacting flows.
Design and implement deep learning-based surrogate modeling frameworks for real-time simulation.
Implement data assimilation and multimodal learning techniques.
Perform validation, verification, and uncertainty quantification.
Leverage GPU-based high-performance computing to enhance the scalability and efficiency of models for complex energy systems.
Publish research findings in top-tier conferences and reputable journals.
Minimum Qualifications:
A Bachelor’s or Master’s degree in mechanical or aerospace engineering, computational science and engineering (CSE), applied mathematics, computational physics, or closely related disciplines.
Strong foundation in Data Science, Artificial Intelligence, Machine Learning, Fluid Dynamics, Turbulence, Combustion, Numerical Methods, and Computational Fluid Dynamics.
Preferred Qualifications:
Familiarity with PINNs, DeepONets, Neural Operators, or similar frameworks.
Hands-on experience with machine learning libraries such as PyTorch or TensorFlow.
Experience with GPU-based computing or high-performance simulation environments.
Excellent communication and scientific writing skills for journal and conference publications.
Strong programming skills in Python, CUDA, C, or C++.
Ability to work independently and collaboratively in a team environment.
What We Offer:
A Graduate Research Assistantship (GRA) with a competitive monthly stipend, tuition waiver, and other benefits as per university policies.
Access to state-of-the-art lab facilities with cutting-edge computational resources, including GPUs.
Opportunities for professional development and participation in impactful research advancing artificial intelligence for science and engineering applications.
How to Apply:
Send your CV along with a cover letter and contact details for 3 references to Prof. Veeraraghava Raju Hasti [ [email protected] ].
Position Start Date: Spring 2025
The position will remain open until filled.
PhDOpportunity GraduateResearch PhDRecruitment ScientificResearch AcademicJobs HigherEducation
MachineLearning ArtificialIntelligence DeepLearning ScientificMachineLearning NeuralNetworks PhysicsInformedAI
ComputationalFluidDynamics TurbulentFlows FluidDynamics
HighPerformanceComputing DataScience NumericalModeling Simulation
Funding details
The position offers a Graduate Research Assistantship (GRA) with a competitive monthly stipend, tuition waiver, and other benefits as per university policies. Access to state-of-the-art lab facilities with cutting-edge computational resources, including GPUs, is provided.
What's required
Applicants must hold a Bachelor’s or Master’s degree in mechanical or aerospace engineering, computational science and engineering, applied mathematics, computational physics, or closely related disciplines. Required skills include a strong foundation in data science, artificial intelligence, machine learning, fluid dynamics, turbulence, combustion, numerical methods, and computational fluid dynamics. Preferred qualifications include familiarity with PINNs, DeepONets, Neural Operators, or similar frameworks; hands-on experience with machine learning libraries such as PyTorch or TensorFlow; experience with GPU-based computing or high-performance simulation environments; excellent communication and scientific writing skills; strong programming skills in Python, CUDA, C, or C++; and the ability to work independently and collaboratively.
How to apply
Send your CV, cover letter, and contact details for three references to Prof. Veeraraghava Raju Hasti at [email protected]. Applications are open for Spring 2025 and will be considered until the position is filled.
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