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Physics Informed Machine Learning Jobs in Memphis, TN

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Physics Informed Machine Learning information

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$5

$19

$24

How much do physics informed machine learning jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for physics informed machine learning in Memphis, TN is $19.49, according to ZipRecruiter salary data. Most workers in this role earn between $12.16 and $24.76 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Memphis, TN? For Physics Informed Machine Learning jobs in Memphis, TN, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Memphis, TN look for? The top searched job categories for Physics Informed Machine Learning jobs in Memphis, TN are:
What cities near Memphis, TN are hiring for Physics Informed Machine Learning jobs? Cities near Memphis, TN with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Sr Staff Image Data Scientist -- Time-Series & Neuroscience

Sr Staff Image Data Scientist -- Time-Series & Neuroscience

St. Jude Children's Research Hospital

Memphis, TN • On-site

Full-time

Posted 7 days ago

St. Jude Children's Research Hospital rating

8.4

Company rating: 8.4 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

60th of 1,003 rated hospitals

Job description

Job Summary:
St. Jude Children's Research Hospital is a leading institution focused on understanding brain development and function through innovative computational research. The Sr Staff Image Data Scientist will be responsible for architecting and developing image analysis platforms, utilizing statistical and machine learning techniques to extract insights from complex biological data.
Responsibilities:
• Develop statistical, time-series, and machine learning techniques to extract meaningful insights from complex biological data (large-scale neuroimages, light and electron microscopy, animal behavior, histopathology, etc).
• Collaborate with scientists and researchers to design experiments and optimize data acquisition protocols for effective downstream computational analysis.
• End-to-end image analysis from pre-processing and data cleaning to reporting results.
• Stay up-to-date with the latest advancements in the field of data science.
Qualifications:
Required:
• A Ph.D. or equivalent degree in mathematics, statistics, computer science, neuroscience, physics or a related field.
• Strong background in statistical analysis and machine learning algorithms.
• Proficiency in programming languages such as Python, R, MATLAB, or similar languages commonly used in scientific computing.
• Strong expertise in time-series analysis, image and signal processing, and data visualization.
• Excellent problem-solving skills and the ability to work independently as well as collaboratively in a team-oriented environment.
• Strong communication skills to effectively convey complex concepts and results to both technical and non-technical stakeholders.
• Bachelor's degree plus 8 years experience required.
• Work experience in relevant area (e.g., applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field).
• Demonstrated technical thought leadership in an applied computational field (e.g., computer vision, deep learning, numerical optimization, image analysis, computer game design, scientific computing, fine element analysis, scientific visualization).
• Substantial experience in image analyses, image data management, and programming (e.g., Python, R, Matlab, Java, C/C++).
• Proven performance in earlier role/comparable role.
Preferred:
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and high-performance computing environments is a plus.
• Master's degree plus six (6) years experience or PhD plus four (4) years experience preferred.
• Experience in biological/medical imaging, deep learning, image analysis platforms (e.g., ImageJ/Fiji, CellProfiler), scientific computing, scientific data visualization, scientific computer code optimization and evaluation in an HPC environment, development of algorithms, statistical methods or scientific software, working with large image data volumes, biological/medical imaging preferred.
Company:
St. Founded in 1962, the company is headquartered in Memphis, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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