Graduate Student Intern - Software Engineering

Cadence; Austin (TX); In loco; USD 85.000 - 120.000; Tempo pieno

Descrizione del lavoro

Cadence Design Systems, Inc. in Austin, TX is seeking a motivated graduate student or researcher to explore AI/ML techniques for geometry, mesh, and graph-structured data.

You will prototype AI-assisted methods for geometry creation, topology optimization, and simulation model preparation, collaborating with researchers and engineers to integrate AI into engineering workflows. The role emphasizes strong fundamentals in data structures and algorithms, C/C++ and Python, debugging and testing, and

Competenze

• Currently pursuing a Master's degree or PhD in Computer Science, Engineering, Applied Mathematics, or a related field.
• Strong foundation in data structures, algorithms, and software engineering principles.
• Programming experience in C/C++ and Python.
• Familiarity with software development practices, including debugging, testing, and version control.
• Strong analytical, problem-solving, collaboration, and communication skills.
• Curiosity and enthusiasm for applying AI technologies to engineering problems.

Mansioni

• Explore and apply AI/ML techniques, including Large Language Models (LLMs), generative AI (GenAI), and Graph Neural Networks (GNNs), to geometry, mesh, and graph-structured engineering data.
• Research and develop AI-driven approaches for geometry modeling, mesh generation, and topology optimization workflows.
• Prototype and evaluate AI-assisted methods for automating geometry creation and simulation model preparation.
• Work with researchers and engineers to integrate AI technologies into engineering and physics-based applications, including thermal and structural simulation.
• Analyze experimental results and improve the quality, robustness, and performance of AI-generated geometry and mesh models.
• Investigate methods to reduce manual modeling effort and accelerate design and simulation workflows through AI automation.
• Contribute to technical discussions, documentation, research reports, and prototype software development.

Conoscenze

C/C++

Python

Data structures

Algorithms

Software engineering

Debugging

Testing

Version control

Collaboration

Communication

AI techniques

Formazione

Master's degree or PhD in Computer Science, Engineering, Applied Mathematics or related field

Strumenti

PyTorch

TensorFlow

Descrizione del lavoro

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Responsibilities

• Explore and apply AI/ML techniques, including Large Language Models (LLMs), generative AI (GenAI), and Graph Neural Networks (GNNs), to geometry, mesh, and graph-structured engineering data.
• Research and develop AI-driven approaches for geometry modeling, mesh generation, and topology optimization workflows.
• Prototype and evaluate AI-assisted methods for automating geometry creation and simulation model preparation.
• Work with researchers and engineers to integrate AI technologies into engineering and physics-based applications, including thermal and structural simulation.
• Analyze experimental results and improve the quality, robustness, and performance of AI-generated geometry and mesh models.
• Investigate methods to reduce manual modeling effort and accelerate design and simulation workflows through AI automation.
• Contribute to technical discussions, documentation, research reports, and prototype software development.

Basic Qualifications

• Currently pursuing a Master's degree or PhD in Computer Science, Engineering, Applied Mathematics, or a related field.
• Strong foundation in data structures, algorithms, and software engineering principles.
• Programming experience in C/C++ and Python.
• Familiarity with software development practices, including debugging, testing, and version control.
• Strong analytical, problem-solving, collaboration, and communication skills.
• Curiosity and enthusiasm for applying AI technologies to engineering problems.

Preferred Qualifications

• Experience with AI/ML, including deep learning, LLMs, GenAI, or GNNs.
• Familiarity with geometric modeling, mesh generation, retopology, computational geometry, or graph-based representations.
• Coursework or research experience in computer graphics, computer-aided engineering (CAE), scientific computing, or simulation.
• Exposure to CAD, CAE, EDA, or simulation-driven design applications.
• Interest in topology optimization, geometry processing, performance optimization, parallel computing, or GPU acceleration.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar tools.

We’re doing work that matters. Help us solve what others can’t.

Equal Employment Opportunity Policy: Cadence is committed to equal employment opportunity throughout all levels of the organization. Read the policy(opens in a new tab) We welcome your interest in the company and want to make sure our job site is accessible to all. If you experience difficulty using this site or to request a reasonable accommodation, please contact [e-mail].

Cadence plays a critical role in creating the technologies that modern life depends on. We are a global electronic design automation company, providing software, hardware, and intellectual property to design advanced semiconductor chips that enable our customers create revolutionary products and experiences. Thanks to the outstanding caliber of the Cadence team and the empowering culture that we have cultivated for over 25 years, Cadence continues to be recognized by Fortune Magazine as one of the 100 Best Companies to Work For. Our shared passion for solving the world’s toughest technical challenges, our dedication to pushing the limits of the industry, and our drive to do meaningful work differentiates the people of Cadence. Cadence is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, basis of disability, or any other protected class.