Build machine learning and physics-informed models to analyze component health and degradation ... Experience with machine learning techniques such as PCA, ANOVA, Clustering, Neural Networks, Time ...
New
Build machine learning and physics-informed models to analyze component health and degradation ... Experience with machine learning techniques such as PCA, ANOVA, Clustering, Neural Networks, Time ...
New
Build physics-informed machine learning models that combine first-principles physics with machine ... neural networks, and Gaussian regression. * Support the complete development lifecycle from ...
Build physics-informed machine learning models that combine first-principles physics with machine ... neural networks, and Gaussian regression. * Support the complete development lifecycle from ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
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Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience with Python (and related ...
Hands-on experience with modern AI frameworks, physics-informed neural networks (PINNs), or industrial Digital Twin platforms (e.g., NVIDIA Omniverse, Siemens Tecnomatix, or equivalent)
Hands-on experience with modern AI frameworks, physics-informed neural networks (PINNs), or industrial Digital Twin platforms (e.g., NVIDIA Omniverse, Siemens Tecnomatix, or equivalent)
Chief Engineer, AI Product Creation
Dearborn, MI · On-site +1
Hands-on experience with modern AI frameworks, physics-informed neural networks (PINNs), or industrial Digital Twin platforms (e.g., NVIDIA Omniverse, Siemens Tecnomatix, or equivalent)
Chief Engineer, AI Product Creation
Dearborn, MI · On-site +1
Hands-on experience with modern AI frameworks, physics-informed neural networks (PINNs), or industrial Digital Twin platforms (e.g., NVIDIA Omniverse, Siemens Tecnomatix, or equivalent)
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ...
Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ...
... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ... Physics Modeling and simulation using numerical computational tool (e.g. MATLAB, ATI, Simulink)
... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ... Physics Modeling and simulation using numerical computational tool (e.g. MATLAB, ATI, Simulink)
Vehicle Prognostics - Applied Data Scientist
Dearborn, MI · On-site
$85K - $160K/yr
... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ... Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ...
Vehicle Prognostics - Applied Data Scientist
Dearborn, MI · On-site
$85K - $160K/yr
... Neural Networks, causal inference, Gaussian regression, etc. * 3+ Experience with Python (and ... Pioneer Physics-Informed Machine Learning (PIML): Fuse first-principles physics modeling with ...
Senior Simulation Vehicle Modeling Engineer
Ann Arbor, MI · On-site +1
$102K - $140K/yr
Physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models ... Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs ...
Senior Simulation Vehicle Modeling Engineer
Ann Arbor, MI · On-site +1
$102K - $140K/yr
Physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models ... Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs ...
Senior Simulation Vehicle Modeling Engineer
$102K - $140K/yr
Physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models ... Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs ...
Senior Simulation Vehicle Modeling Engineer
$102K - $140K/yr
Physics-based modeling of ground vehicles, including longitudinal/lateral dynamics, tire models ... Familiarity with how learned models (neural networks) consume simulation and vehicle model outputs ...
Stay informed of emerging technologies and trends in AI/ML, recommending innovative approaches to ... Familiarity with deep learning techniques, neural networks, and natural language processing.
Stay informed of emerging technologies and trends in AI/ML, recommending innovative approaches to ... Familiarity with deep learning techniques, neural networks, and natural language processing.
Stay informed of emerging technologies and trends in AI/ML, recommending innovative approaches to ... Familiarity with deep learning techniques, neural networks, and natural language processing.
Stay informed of emerging technologies and trends in AI/ML, recommending innovative approaches to ... Familiarity with deep learning techniques, neural networks, and natural language processing.
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 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 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 popular job titles related to Physics Informed Neural Networks jobs in Michigan? For Physics Informed Neural Networks jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Physics Informed Neural Networks jobs in Michigan look for? The top searched job categories for Physics Informed Neural Networks jobs in Michigan are:
What cities in Michigan are hiring for Physics Informed Neural Networks jobs? Cities in Michigan with the most Physics Informed Neural Networks job openings:
Job description
Job Summary
We are seeking a highly motivated Scientist / Research Engineer to develop and deploy advanced prognostics and predictive maintenance solutions for vehicle systems. The ideal candidate will leverage data science, machine learning, physics-based modeling, and signal processing techniques to predict component degradation and estimate Remaining Useful Life (RUL) for automotive applications.
Key Responsibilities
- Develop prognostic and predictive maintenance algorithms using vehicle and connected vehicle data.
- Build machine learning and physics-informed models to analyze component health and degradation.
- Process and analyze large datasets using Python, SQL, and cloud platforms.
- Develop fault detection and anomaly detection solutions for vehicle systems.
- Perform modeling and simulation using MATLAB/Simulink.
- Collaborate with cross-functional teams to deploy solutions into production vehicles.
- Support embedded software implementation in C++ environments.
Required Skills
- Python
- SQL
- C++
- Data Science & Machine Learning
- MATLAB / Simulink
- Algorithms & Statistical Analysis
- Google Cloud Platform (Google Cloud Platform) or other cloud environments
- Signal Processing (DSP)
- Predictive Analytics & Prognostics
Required Qualifications
- Master''s degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Mathematics, Physics, or related field.
- 4+ years of experience applying statistical and machine learning techniques.
- 3+ years of experience with Python and SQL.
- Experience with predictive modeling, sensor data analysis, and vehicle diagnostics.
- Strong analytical and problem-solving skills.
Preferred Qualifications
- PhD in a related technical field.
- Experience in Automotive, Connected Vehicle, EV, Controls, Robotics, or Prognostics & Health Management (PHM).
- Knowledge of Spark, Hadoop, ATI, ETAS, and embedded systems.
- Experience with machine learning techniques such as PCA, ANOVA, Clustering, Neural Networks, Time Series Forecasting, and Causal Inference.