The focus involves the optimization of various common neural networks for optimal performance on ... Requirements: * Degree in Computer Science, Engineering, Math, Physics, or related field ...
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The focus involves the optimization of various common neural networks for optimal performance on ... Requirements: * Degree in Computer Science, Engineering, Math, Physics, or related field ...
AI & GenAI Data Scientist - Manager
$99K - $232K/yr
... informed decision-making and driving business growth. Within our Technology Consulting practice ... Applying deep learning techniques and neural networks to improve predictive analytics ...
New
AI & GenAI Data Scientist - Manager
$99K - $232K/yr
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Portland, OR · On-site
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... informed decision-making and driving business growth. Within our Internal Firm Services practice ... neural networks and deep learning methods for advanced AI applications - Managing data quality and ...
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Portland, OR · On-site
$50K - $112K/yr
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Assistant/Associate/Full Professor of Bioengineering: Synthetic Biology (2 positions)
Eugene, OR · On-site
... networks; and multi-omics integration and quantitative modeling to guide the design and engineering ... neural engineering, and synthetic biology. With the opening of its second research facility, the ...
... networks; and multi-omics integration and quantitative modeling to guide the design and engineering ... neural engineering, and synthetic biology. With the opening of its second research facility, the ...
... networks; and multi-omics integration and quantitative modeling to guide the design and engineering ... neural engineering, and synthetic biology. With the opening of its second research facility, the ...
Physics Informed Neural Networks information
What is a physics informed neural network?
A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.
What does a physics informed neural network do?
In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.
What are the key skills and qualifications needed to thrive in physics informed neural networks?
To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.
What job categories do people searching Physics Informed Neural Networks jobs in Oregon look for?
The top searched job categories for Physics Informed Neural Networks jobs in Oregon are:
$129K - $171K/yr
Full-time
Medical
Re-posted 3 days ago
Job description
Senior Neural Network Kernel Software Development Engineer
Our client is making substantial investments in software to enhance the seamless deployment of neural networks on their hardware, streamlining the experience for researchers and developers. The focus involves the optimization of various common neural networks for optimal performance on architectures, facilitated by the software optimization tool flow.
We are seeking software developers who are driven and naturally curious. The chosen candidate will contribute within agile teams, working closely with senior software engineers for mentorship. This role presents an opportunity to tackle novel challenges using cutting-edge technologies, as they build innovative systems from scratch.
As a key team member, you will specialize in constructing efficient implementations of practical neural net kernels tailored to their distinctive hardware architecture. Additionally, you will implement diverse computing algorithms, maximizing computation and communication throughput. This role involves developing a profound understanding of the architecture's intricacies, working collaboratively with the architects and compiler engineers.
Responsibilities:
- Experience writing kernels to accelerate Neural Network execution on custom hardware accelerators (not on CPU's)
- Design, prototype, and execute low-level, adaptable C++ programs (kernels) for various neural net operations.
- Define, document, and communicate configuration APIs for these kernels to the compiler team.
- Share performance optimization concepts with both compiler engineers and architects working on future product generations.
- Develop comprehensive computation strategies spanning kernels for multichannel and multi-chip neural net implementations.
Requirements:
- Degree in Computer Science, Engineering, Math, Physics, or related field (preferably MS or PhD).
- Profound knowledge of modern C++, with a focus on code generation and low-level compute optimizations.
- Familiarity with fundamental Neural Network operator algorithms - Convolutions, Transformers, RNNs.
- Demonstrated capability to independently navigate challenging, well-defined problems.
- Aptitude and interest in both high-level conceptual understanding and intricate technical details.
- Enthusiasm for problem-solving within highly structured and restricted environments.
Preferred Skills and Experience:
- Proficiency in Python.
- Experience with other AI accelerator programming.
- Strong mathematical aptitude.
- Enjoyment of solving complex problems.
Our client offers:
- Comprehensive health and extended health benefits.
- Competitive Salary
- Unlimited sick leave.
- Stock options.
- Contribution to revolutionizing chip and software technologies with global impact.
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